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• Applications of Evolutionary Computation
• Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications
• Computational Intelligence for Sustainability
• Evolutionary Computation in Edge, Fog, and Cloud Computing
• Evolutionary Machine Learning
• Machine Learning and AI in Digital Healthcare and Personalized Medicine
• Resilient Bio-Inspired Algorithms
• Soft Computing applied to Games
• Surrogate-Assisted Evolutionary Optimisation.

This book constitutes the refereed proceedings of the 25th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of Evo*2023, in April 2023, co-located with the Evo*2023 events EuroGP, EvoCOP, and EvoMUSART. The EuroGP focused on the technique of genetic programming, EvoCOP targeted evolutionary computation in combinatorial optimization, and EvoMUSART was dedicated to evolved and bio-inspired music, sound, art, and design. The EvoApplications 2023 presents papers on the different areas: Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications, Applications of Bio-inspired Techniques on Social Networks, Evolutionary Computation in Edge, Fog, and Cloud Computing, Evolutionary Computation in Image Analysis, Signal Processing, and Pattern Recognition and others.

• pt. 1. EvoApplications 2011 : EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, Torino, Italy, April 27-29, 2011, proceedings
• pt. 2. EvoApplications 2011 : EvoCOMNET, EvoFIN, EvoHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOG, Torino, Italy, April 27-29, 2011, proceedings.

This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2011, held in Torino, Italy, in April 2011 colocated with the Evo 2011 events. Thanks to the large number of submissions received, the proceedings for EvoApplications 2011 are divided across two volumes (LNCS 6624 and 6625). The present volume contains contributions for EvoComnet, EvoFin, EvoIhot, EvoMusart, EvoStim, and EvoTransloc. The 51 revised full papers presented were carefully reviewed and selected from numerous submissions. This volume presents an overview about the latest research in EC. Areas where evolutionary computation techniques have been applied range from telecommunication networks to complex systems, finance and economics, games, image analysis, evolutionary music and art, parameter optimization, scheduling, and logistics. These papers may provide guidelines to help new researchers tackling their own problem using EC.
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• [I]. Engineering and real-world applications: 1. A comparison of different many-objective optimization algorithms for energy system optimization / Tobias Rodemann
• 2. Design of powered floor systems for mobile robots with differential evolution / Eric Medvet, Stefano Seriani, Alberto Bartoli, and Paolo Gallina
• 3. Solving the multi-objective flexible job-shop scheduling problem with alternative recipes for a chemical production process / Piotr Dziurzanski, Shuai Zhao, Jerry Swan, Leandro Soares Indrusiak, Sebastian Scholze, and Karl Krone
• 4. Quantifying the effects of increasing user choice in MAP-elites applied to a workforce scheduling and routing problem / Neil Urquhart, Emma Hart, and William Hutcheson
• 5. A hybrid multi-objective differential evolution approach to stator winding optimization / André M. Silva, Fernando J.T.E. Ferreira, and Carlos Henggeler Antunes
• 6. GA-Novo : de novo peptide sequencing via tandem mass spectrometry using genetic algorithm / Samaneh Azari, Bing Xue, Mengjie Zhang, and Lifeng Peng
• 7. Ant colony optimization for optimized operation scheduling of combined heat and power plants / Johannes Mast, Stefan Rädle, Joachim Gerlach, and Oliver Bringmann
• 8. A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness-distance analysis / Maciej Komosinski and Agnieszka Mensfelt.

• [II]. Games: 9. Free form evolution for Angry Birds level generation / Laura Calle, Juan J. Merelo, Antonio Mora-García, and José-Mario García-Valdez
• 10. Efficient online hyperparameter adaptation for deep reinforcement learning / Yinda Zhou, Weiming Liu, and Bin Li
• 11. GAMER : a genetic algorithm with motion encoding reuse for action-adventure video games / Tasos Papagiannis, Georgios Alexandridis, and Andreas Stafylopatis
• 12. Effects of input addition in learning for adaptive games : towards learning with structural changes / Iago Bonnici, Abdelkader Gouaïch, and Fabien Michel.

• [III]. General: 13. Supporting medical decisions for treating rare diseases through genetic programming / Illya Bakurov, Mauro Castelli, Leonardo Vanneschi, and Maria João Freitas
• 14. Evolutionary successful strategies in a transparent iterated prisoner's dilemma / Anton M. Unakafov, Thomas Schultze, Igor Kagan, Sebastian Moeller, Alexander Gail, Stefan Treue, Stephan Eule, and Fred Wolf
• 15. Evolutionary algorithms for the design of quantum protocols / Walter Krawec, Stjepan Picek, and Domagoj Jakobovic
• 16. Evolutionary computation techniques for constructing SAT-based attacks in algebraic cryptanalysis / Artem Pavlenko, Alexander Semenov, and Vladimir Ulyantsev
• 17. On the use of evolutionary computation for in-silico medicine : modelling sepsis via evolving continuous petri nets / Ahmed Hallawa, Elisabeth Zechendorf, Yi Song, Anke Schmeink, Arne Peine, Lukas Marin, Gerd Ascheid, and Guido Dartmann
• 18. A cultural algorithm for determining similarity values between users in recommender systems / Kalyani Selvarajah, Ziad Kobti, and Mehdi Kargar.

• [IV]. Image and signal processing: 19. Optimizing the C index using a canonical genetic algorithm / Thomas A. Runkler and James C. Bezdek
• 20. Memetic evolution of classification ensembles / Szymon Piechaczek, Michal Kawulok, and Jakub Nalepa
• 21. Genetic programming for feature selection and feature combination in salient object detection / Shima Afzali, Harith Al-Sahaf, Bing Xue, Christopher Hollitt, and Mengjie Zhang
• 22. Variable-length representation for EC-based feature selection in high-dimensional data / N.D. Cilia, C. De Stefano, F. Fontanella, and A. Scotto di Freca.

• [V]. Life sciences: 23. A knowledge based differential evolution algorithm for protein structure prediction / Pedro H. Narloch and Márcio Dorn
• 24. A biased random key genetic algorithm with local search chains for molecular docking / Pablo F. Leonhart and Márcio Dorn
• 25. Self-sustainability challenges of plants colonization strategies in virtual 3D environments / Kevin Godin-Dubois, Sylvain Cussat-Blanc, and Yves Duthen.

• [VI]. Networks and distributed systems: 26. Early detection of Botnet activities using grammatical evolution / Selim Yilmaz and Sevil Sen
• 27. Exploring concurrent and stateless evolutionary algorithms / Juan J. Merelo, J.L.J. Laredo, Pedro A. Castillo, José-Mario García-Valdez, and Sergio Rojas-Galeano
• 28. Evolving trust formula to evaluate data trustworthiness in VANETs using genetic programming / Mehmet Aslan and Sevil Sen
• 29. A matheuristic for green and robust 5G virtual network function placement / Thomas Bauschert, Fabio D'Andreagiovanni, Andreas Kassler, and Chenghao Wang
• 30. Prolong the network lifetime of wireless underground sensor networks by optimal relay node placement / Nguyen Thi Tam, Huynh Thi Thanh Binh, Tran Huy Hung, Dinh Anh Dung, and Le Trong Vinh.

• [VII]. Neuroevolution and data analytics: 31. The evolution of self-taught neural networks in a multi-agent environment / Nam Le, Anthony Brabazon, and Michael O'Neill
• 32. Coevolution of generative adversarial networks / Victor Costa, Nuno Lourenço, and Penousal Machado
• 33. Evolving recurrent neural networks for time series data prediction of coal plant parameters / AbdElRahman ElSaid, Steven Benson, Shuchita Patwardhan, David Stadem, and Travis Desell
• 34. Improving NeuroEvolution efficiency by surrogate model-based optimization with phenotypic distance kernels / Jörg Stork, Martin Zaefferer, and Thomas Bartz-Beielstein.

• [VIII]. Numerical optimization : theory, benchmarks and applications: 35. Compact optimization algorithms with re-sampled inheritance / Giovanni Iacca and Fabio Caraffini
• 36. Particle swarm optimization : understanding order-2 stability guarantees / Christopher W. Cleghorn
• 37. Fundamental flowers : evolutionary discovery of coresets for classification / Pietro Barbiero and Alberto Tonda.

This book constitutes the refereed proceedings of the 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoMUSART. The 44 revised full papers presented were carefully reviewed and selected from 66 submissions. They were organized in topical sections named: Engineering and Real World Applications; Games; General; Image and Signal Processing; Life Sciences; Networks and Distributed Systems; Neuroevolution and Data Analytics; Numerical Optimization: Theory, Benchmarks, and Applications; Robotics.
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• Parameter Setting in EAs: a 30 Year Perspective.- Parameter Control in Evolutionary Algorithms.- Self-Adaptation in Evolutionary Algorithms.- Adaptive Strategies for Operator Allocation.- Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms.- Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks.- Genetic Programming: Parametric Analysis of Structure Altering Mutation Techniques.- Parameter Sweeps for Exploring Parameter Spaces of Genetic and Evolutionary Algorithms.- Adaptive Population Sizing Schemes in Genetic Algorithms.- Population Sizing to Go: Online Adaptation Using Noise and Substructural Measurements.- Parameter-less Hierarchical Bayesian Optimization Algorithm.- Evolutionary Multi-Objective Optimization Without Additional Parameters.- Parameter Setting in Parallel Genetic Algorithms.- Parameter Control in Practice.- Parameter Adaptation for GP Forecasting Applications.
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One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
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This book constitutes the refereed proceedings for the 4th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2004, held in Coimbra, Portugal, in April together with EuroGP 2004 and six workshops on evolutionary computing. The 23 revised full papers presented were carefully reviewed and selected from 86 submissions. Among the topics addressed are evolutionary algorithms as well as metaheuristics like memetic algorithms, ant colony optimization, and scatter search; the papers are dealing with representations, operators, search spaces, adaptation, comparison of algorithms, hybridization of different methods, and theory. Among the combinatorial optimization problems studied are graph coloring, network design, cutting, packing, scheduling, timetabling, traveling salesman, vehicle routing, and various other real-world applications.
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This book constitutes the refereed proceedings of three workshops on the application of evolutionary programming and algorithms in various domains; these workshops were held in conjunction with the 5th European Conference on Genetic Programming, EuroGP 2002, in Kinsale, Ireland, in April 2002. The 33 revised full papers presented were carefully reviewed and selected by the respective program committees. In accordance with the three workshops EvoCOP, EvoIASP, and EvoSTIM/EvoPLAN, the papers are organized in topical sections on combinatorial optimization problems; image analysis and signal processing; and scheduling, timetabling, and AI planning.
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This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2005, held in Lausanne, Switzerland in March/April 2005.The 24 revised full papers presented were carefully reviewed and selected from 66 submissions. The papers cover evolutionary algorithms as well as related approaches like scatter search, simulated annealing, ant colony optimization, immune algorithms, variable neighborhood search, hyperheuristics, and estimation of distribution algorithms. The papers deal with representations, analysis of operators and fitness landscapes, and comparison algorithms. Among the combinatorial optimization problems studied are graph coloring, quadratic assignment, knapsack, graph matching, packing, scheduling, timetabling, lot-sizing, and the traveling salesman problem.
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• Theory of Evolutionary Computing (I).- Optimal Fixed and Adaptive Mutation Rates for the LeadingOnes Problem.- Mirrored Sampling and Sequential Selection for Evolution Strategies.- Optimisation and Generalisation: Footprints in Instance Space.- Adaptive Drift Analysis.- Optimizing Monotone Functions Can Be Difficult.- Log-Linear Convergence of the Scale-Invariant (?/? w , ?)-ES and Optimal ? for Intermediate Recombination for Large Population Sizes.- Exploiting Overlap When Searching for Robust Optima.- Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis.- One-Point Geometric Crossover.- When Does Dependency Modelling Help? Using a Randomized Landscape Generator to Compare Algorithms in Terms of Problem Structure.- First-Improvement vs. Best-Improvement Local Optima Networks of NK Landscapes.- Differential Mutation Based on Population Covariance Matrix.- General Lower Bounds for the Running Time of Evolutionary Algorithms.- A Binary Encoding Supporting Both Mutation and Recombination.- Towards Analyzing Recombination Operators in Evolutionary Search.- Theory of Evolutionary Computing (II).- Bidirectional Relation between CMA Evolution Strategies and Natural Evolution Strategies.- A Fine-Grained View of GP Locality with Binary Decision Diagrams as Ant Phenotypes.- Drift Analysis with Tail Bounds.- More Effective Crossover Operators for the All-Pairs Shortest Path Problem.- Comparison-Based Adaptive Strategy Selection with Bandits in Differential Evolution.- Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation.- An Archive Maintenance Scheme for Finding Robust Solutions.- Experimental Supplements to the Theoretical Analysis of Migration in the Island Model.- General Scheme for Analyzing Running Times of Parallel Evolutionary Algorithms.- Negative Drift in Populations.- Log(?) Modifications for Optimal Parallelism.- The Linkage Tree Genetic Algorithm.- An Analysis of the XOR Dynamic Problem Generator Based on the Dynamical System.- The Role of Degenerate Robustness in the Evolvability of Multi-agent Systems in Dynamic Environments.- Machine Learning, Classifier Systems, Image Processing.- Evolutionary Learning of Technical Trading Rules without Data-Mining Bias.- Using Computational Intelligence to Identify Performance Bottlenecks in a Computer System.- Selecting Small Audio Feature Sets in Music Classification by Means of Asymmetric Mutation.- Globally Induced Model Trees: An Evolutionary Approach.- Open-Ended Evolutionary Robotics: An Information Theoretic Approach.- A Novel Similarity-Based Crossover for Artificial Neural Network Evolution.- Indirect Encoding of Neural Networks for Scalable Go.- Comparison-Based Optimizers Need Comparison-Based Surrogates.- A Cooperative Coevolutionary Approach to Partitional Clustering.- Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task.- Incorporating Domain Knowledge into Evolutionary Computing for Discovering Gene-Gene Interaction.- The Application of Pittsburgh-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis in Association Studies.- Threshold Selection, Mitosis and Dual Mutation in Cooperative Co-evolution: Application to Medical 3D Tomography.- Comparative Analysis of Search and Score Metaheuristics for Bayesian Network Structure Learning Using Node Juxtaposition Distributions.- Analyzing the Credit Default Swap Market Using Cartesian Genetic Programming.- Memetic Algorithms, Hybridized Techniques, Meta and Hyperheurisics.- A Memetic Cooperative Optimization Schema and Its Application to the Tool Switching Problem.- Ownership and Trade in Spatial Evolutionary Memetic Games.- A Hyper-Heuristic Approach to Strip Packing Problems.- Asymptotic Analysis of Computational Multi-Agent Systems.- Path-Guided Mutation for Stochastic Pareto Local Search Algorithms.- Scheduling English Football Fixtures over the Holiday Period Using Hyper-heuristics.- Graph Clustering Based Model Building.- How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms.- Secure and Task Abortion Aware GA-Based Hybrid Metaheuristics for Grid Scheduling.- A Memetic Algorithm for the Pickup and Delivery Problem with Time Windows Using Selective Route Exchange Crossover.- Ant Based Hyper Heuristics with Space Reduction: A Case Study of the p-Median Problem.- A Study of Multi-parent Crossover Operators in a Memetic Algorithm.- A Hybrid Genetic Algorithm for the Traveling Salesman Problem Using Generalized Partition Crossover.- A Memetic Algorithm with Non Gradient-Based Local Search Assisted by a Meta-model.- Multiobjective Optimization, Theoretical Aspects.- Theoretically Investigating Optimal ?-Distributions for the Hypervolume Indicator: First Results for Three Objectives.- Convergence Rates of (1+1) Evolutionary Multiobjective Optimization Algorithms.- Tight Bounds for the Approximation Ratio of the Hypervolume Indicator.- Evolutionary Multiobjective Optimization Algorithm as a Markov System.- A Natural Evolution Strategy for Multi-objective Optimization.- Solving Multiobjective Optimization Problem by Constraint Optimization.- Enhancing Diversity for Average Ranking Method in Evolutionary Many-Objective Optimization.- Objective Space Partitioning Using Conflict Information for Many-Objective Optimization.- How Crossover Speeds Up Evolutionary Algorithms for the Multi-criteria All-Pairs-Shortest-Path Problem.- Path Relinking on Many-Objective NK-Landscapes.- In Search of Equitable Solutions Using Multi-objective Evolutionary Algorithms.- Stopping Criteria for Genetic Algorithms with Application to Multiobjective Optimization.- Defining and Optimizing Indicator-Based Diversity Measures in Multiobjective Search.- On Expected-Improvement Criteria for Model-based Multi-objective Optimization.- Parameter Tuning Boosts Performance of Variation Operators in Multiobjective Optimization.
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We are very pleased to present to you this LNCS volume, the proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN 2010). PPSN is one of the most respected and highly regarded c- ference series in evolutionary computation, and indeed in natural computation aswell.Thisbiennialeventwas?rstheldinDortmundin1990, andtheninBr- sels (1992), Jerusalem (1994), Berlin (1996), Amsterdam (1998), Paris (2000), Granada (2002), Birmingham (2004), Reykjavik (2006) and again in Dortmund in 2008. PPSN 2010 received 232 submissions. After an extensive peer review p- cess involving more than 180 reviewers, the program committee chairs went through all the review reports and ranked the papers according to the revi- ers'comments. Each paper wasevaluated by at least three reviewers.Additional reviewers from the appropriate branches of science were invoked to review into disciplinary papers. The top 128 papers were ?nally selected for inclusion in the proceedings and presentation at the conference. This represents an acceptance rate of 55%, which guarantees that PPSN will continue to be one of the c- ferences of choice for bio-inspired computing and metaheuristics researchers all over the world who value the quality over the size of a conference. The papers included in the proceedingsvolumes covera wide range of topics, fromevolutionarycomputationto swarmintelligence, frombio-inspiredcomp- ing to real-world applications. Machine learning and mathematical games s- portedbyevolutionaryalgorithmsaswellasmemetic, agent-orientedsystemsare also represented. They all are the latest and best in natural computation. The proceedings are composed of two volumes divided into nine thematic sections.
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• EvoCOMNET contributions
• EvoFIN contributions
• EvoIASP contributions -- EvoINTERACTION contributions
• EvoMUSART contributions
• EvoSTOC contributions
• EvoTRANSLOG contributions.

This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2007, held in Valencia, Spain in April 2007. It examines evolutionary computation in communications, networks, and connected systems; finance and economics; image analysis and signal processing; and transportation and logistics. Coverage also details evolutionary algorithms in stochastic and dynamic environments.
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• EvoBIO contributions
• EvoCOMNET contributions
• EvoHOT contributions
• EvoIASP contributions
• EvoINTERACTION contributions
• EvoMUSART contributions
• EvoSTOC contributions.

This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2006, held in Budapest, Hungary, in April 2006. The 65 revised full papers and 13 revised short papers presented were carefully reviewed and selected from a total of 149 submissions. In accordance with the seven workshops covered, the papers are organized in topical sections on evolutionary bioinformatics, evolutionary computation in communications, networks, and connected systems, evolutionary computation in hardware optimization, evolutionary computation in image analysis and signal processing, interactive evolution and humanized computational intelligence, evolutionary music and art, and evolutionary algorithms in stochastic and dynamic environments.
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This book constitutes the refereed proceedings of the 9th International Conference on Parallel Problem Solving from Nature, PPSN 2006, held in Reykjavik, Iceland in September 2006. The 106 revised full papers presented were carefully reviewed and selected from 255 submissions. The papers cover a wide range of topics, from evolutionary computation to swarm intelligence and from bio-inspired computing to real-world applications; they are organized in topical sections on theory, new algorithms, applications, multi-objective optimization, evolutionary learning, as well as representations, operators, and empirical evaluation.
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This book constitutes the refereed joint proceedings of six workshops on evolutionary computing, EvoWorkshops 2005, held in Lausanne, Switzerland in March/April 2005. The 56 revised full papers presented were carefully reviewed and selected from a total of 143 submissions. In accordance with the six workshops covered, the papers are organized in topical sections on evolutionary bioinformatics; evolutionary computing in communications, networks, and connected systems; hardware optimization techniques; evolutionary computation in image analysis and signal processing; evolutionary music and art; and evolutionary algorithms in stochastic and dynamic environments.
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This book constitutes the joint refereed proceedings of six workshops on evolutionary computing, EvoWorkshops 2004, held together with EuroGP 2004 and EvoCOP 2004 in Coimbra, Portugal, in April 2004. The 55 revised full papers presented were carefully reviewed and selected from a total of 123 submissions. In accordance with the six workshops covered, the papers are organized in topical sections on evolutionary bioinformatics; evolutionary computing in communications, networks, and connected systems; hardware optimization techniques; evolutionary computing in image analysis and signal processing; evolutionary music and art; and evolutionary algorithms in stochastic and dynamic environments.
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• Preface. Committee and Sponsors. Evolutionary computation in crack problems
• W. Beluch. Investigation of evolutionary algorithm effectiveness in optimal synthesis of certain mechanisms
• K. Bialas-Hetltowski, et al. Minimum heat losses subjected to stiffness constraints: window frame optimization
• R.A. Bialecki, M. Krol. Evolutionary computation in inverse problems
• T. Burczynski, et al. Hang-glider wing design by genetic optimization
• S. D'Angelo, et al. An error function for optimum dimension synthesis of mechanisms using genetic algorithms
• I.F. de Bustos, et al. Evolutionary computation in thermoelastic problems
• A. Dlugosz. Management of evolutionary MAS for multiobjective optimisation
• G. Dobrowalski, M. Kisiel-Dorohinicki. PAMUC: a new method to handle with constraints and multiobjectivity in evolutionary algorithms
• R. Filomeno Coelho, et al. A comparative analysis of "controlled elitism" in the NGSA-II applied to frame optimization
• D. Greiner, et al. IS-PAES: multiobjective optimization with efficient constraint handling
• A. Hernandez Aguirre, et al. Optimization of aligned fiber laminate composites
• Z. Hu, et al. Genetic algorithm for damage assessment
• V.T. Johnson, et al. Estimation of parameters for a hydrodynamic transmission system mathematical model with the application of genetic algorithm
• A. Kesy, et al. Study of safety of high-rise buildings using evolutionary search
• S. Khajhpour, D.E. Grierson. Structural design using genetic algorithm
• E. Kita, et al. The topology optimization using evolutionary search
• G. Kokot, P. Orantek. Identification of CMM parametric errors by hierarchical genetic strategy
• J. Kolodziej, et al. Genetic algorithm for fatigue crack detection in Timoshenko beam
• M. Krawczuk, et al. Multicriteria design optimization of robot gripper mechanisms
• S. Krenich. Optimal design of multiple clutch brakes using a multistage evolutionary method
• S. Krenich, A. Osyczka. Distributed evolutionary algorithms in optimization of nonlinear solids
• W. Kus, T. Burczynski. Adaptive penalty strategies in genetic search for problems with inequality and equality constraints
• C.-Y. Lin, W.-H. Wu. On the identification of linear elastic mechanical behaviour of orthopedic materials using evolutionary algorithms
• M. Magalhaes Dourado, et al. Ranking pareto optimal solutions in genetic algorithm by using undifferentiation interval method
• J. Montusiewicz. The effectiveness of probabilistic algorithms in shape and topology discrete optimisation of 2-D composite structures
• A. Muc. Genetic algorithms in optimisation of resin hardening technological processes
• A. Muc, P. Saj. Hybrid evolutionary algorithms in optimization of structures under dynamical loads
• P. Orantek. Evolutionary optimization system (EOS) for design automation
• O. Osyczka, et al. Evolutionary method for a universal motor geometry optimization
• G. Papa, B. Korousic-Seljak. A review of the development and application of cluster oriented genetic algorithms
• I.C. Parmee. Genetic algorithm optimization of hole shapes in a perforated elastic plate over a range of loads
• S. Vigdergauz. An object oriented library for evolutionary programs with applications in partitioning of finite element meshes
• J. Zola, et al.
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This book contains papers presented at the IUTAM Symposium on Evolutionary Methods in Mechanics held in Cracow, Poland, September 24-27, 2002. Recently, Evolutionary algorithms and methods have become the most effective tools for solving specific kinds of problems in mechanics, especially in structural and multidisciplinary optimization. The book is devoted to both theoretical and practical developments of computational mechanics methods drawing their inspiration from nature with particular emphasis on evolutionary models of computation such as genetic algorithms, evolutionary strategies, classifier systems, evolutionary programming and other evolutionary computation techniques in mechanics. The special emphasis is put on evolutionary optimization in various fields of mechanics. The subject of evolutionary optimization has recently experienced a remarkable growth. New concepts, approaches and applications are being continually and exploited to provide efficient tools for solving a variety of optimization problems in mechanics. Several important topics are presented: evolutionary methods in shape and topology optimization, evolutionary methods in size and material optimization, evolutionary methods in multiobjective optimization, in inverse problems of engineering mechanics, in biomechanics, coupling of evolutionary methods and neural networks in mechanics, methods of artificial intelligence in mechanics based on evolutionary approaches and other unconventional applications in mechanics. Research workers, specialists and professionals who deal with methods of artificial intelligence, especially in the field of evolutionary computation, structural and multidisciplinary optimization would be interested in this book.
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This book constitutes the joint refereed proceedings of six workshops, EvoWorkshops 2003, held together with EuroGP 2003 in Essex, UK in April 2003.The 63 revised full papers presented were carefully reviewed and selected from a total of 109 submissions. In accordance with the six workshops covered , the papers are organized in topical sections on bioinformatics, combinatorial optimization, image analysis and signal processing, evolutionary music and art, evolutionary robotics, and scheduling and timetabling.
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This book constitutes the refereed proceedings of the 7th International Conference on Parallel Problem Solving from Nature, PPSN 2002, held in Granada, Spain in September 2002. The 90 revised full papers presented were carefully reviewed and selected from 181 submissions. The papers are organized in topical sections on evolutionary algorithms theory, representation and codification, variation operators, evolutionary techniques and coevolution, multiobjective optimization, new techniques for evolutionary algorithms, hybrid algorithms, learning classifier systems, implementation of evolutionary algorithms, applications, and cellular automata and ant colony optimization.
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This book constitutes the refereed proceedings of five application-oriented workshops held concurrently as EvoWorkshops 2001 in Como, Italy in April 2001. The 52 revised full papers presented were carefully reviewed and selected out of 75 submissions. The papers are organized in topical sections on graph problems, Knapsack problems, ant algorithms, assignment problems, evolutionary algorithms analysis, permutative problems, aeronautics, image analysis and signal processing, evolutionary learning, and evolutionary scheduling and timetabling.
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• Simulating pricing behaviours using a genetic algorithm / Sue Bedingfield, Stephen Huxford, Yen Cheung
• Biologically inspired computational ecologies : a case study / Paul Devine, Ray Paton
• Modelling bounded rationality using evolutionary techniques / Bruce Edmonds, Scott Moss
• The abstract theory of evolution of the living / V.L. Kalmykov
• An evolutionary algorithm for single objective nonlinear constrained optimization problems / Hunter P. Albright, James P. Ignizio
• On recombinative sampling / Ian East
• The evolution of mutation, plasticity and culture in cyclically changing environments ; On the structure and transformation of landscapes / Tony Hirst
• Island model genetic algorithms and linearly separable problems / Darrell Whitley, Soraya Rana, Robert Heckendorn
• Empirical validation of the performance of a class of transient detector / Philip Jacob, Andrew Ball
• The construction and evaluation of decision trees : a comparison of evolutionary and concept learning methods / H. Kennedy ... [et al.]
• Parallel distributed genetic programming applied to the evolution of natural language recognisers / Riccardo Poli
• Scheduling planned maintenance of the South Wales region of the national grid / Bill Langdon
• Solving generic scheduling problems with a distributed genetic algorithm / Malcolm McIlhagga
• Directing the search of evolutionary and neighbourhood-search optimisers for the flowshop sequencing problem with an idle-time heuristic / Peter Ross, Andrew Tuson
• Multiobjective genetic algorithms for pump scheduling in water supply / Dragan Savic, Godfrey Walters, Martin Schwab
• Use of rules and preferences for schedule builders in genetic algorithms for production scheduling / Jane Shaw, Peter Fleming
• A voxel based approach to evolutionary shape optimisation / Peter Baron ... [et al.]
• Phase transition networks : a modelling technique supporting the evolution of autonomous agents' tactical and operational activities / Anthony Deakin, Derek Yates
• An evolutionary, agent-assisted strategy for conceptual design space decomposition / Ian Parmee, M. Beck
• Task scheduling with use of classifier systems / Franciszek Seredýnski.

This book constitutes the refereed post-workshop proceedings of the AISB International Workshop on Evolutionary Computing, held in Manchester, UK, in April 1997.The 22 strictly reviewed and revised full papers presented were selected for inclusion in the book after two rounds of refereeing. The papers are organized in sections on evolutionary approaches to issues in biology and economics, problem structure and finite landscapes, evolutionary machine learning and classifier systems, evolutionary scheduling, and more techniques and applications of evolutionary algorithms.
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• Evolutionary Computation & Swarm Intelligence
• Surrogate Model-Assisted Evolutionary Algorithms for Parameter Identification of Electrochemical Model of Lithium-Ion Battery: A Comparison Study
• Research on Multi-modal Multi-Objective Path Planning by Improved Ant Colony Algorithm
• Local Path Planning Algorithm Designed for Unmanned Surface Vessel Based on Improved Genetic Algorithm
• A Multi-Objective Particle Swarm Algorithm Based on a Preference Strategy
• An Improved Harris Hawk Optimization Algorithm Based on Spiral Search and Neighborhood Perturbation
• S-Plane Controller Parameter Tuning Based on IAFSA for UUV
• A Reinforcement-Learning-Driven Bees Algorithm for Large-Scale Earth Observation Satellite Scheduling
• Optimal Formation of UUV Groups Based on Shape Theory and Improved Ant Colony Algorithm Under Communication Delay
• Global Path Planning for Unmanned Ships Based on Improved Particle Swarm Algorithm
• A Self-Adaptive Single-objective Multitasking Optimization Algorithm
• Improved Whale Optimization Algorithm by Multi-mechanism Fusion
• Multi-stage Objective Function Optimized Hand-Eye Self-calibration of Robot in Autonomous Environment
• An Improved Chaos-based Particle Swarm Optimization Algorithm
• Task Location Distribution based Genetic Algorithm for UAV Mobile Crowd Sensing
• The Utilities of Evolutionary Multiobjective Optimization for Neural Architecture Search An Empirical Perspective
• Research on Unmanned Ship Collision Avoidance Algorithm based on Improved Particle Swarm Pptimization Algorithm
• Solving Constrained Multi-objective Optimization Problems with Passive Archiving Mechanism
• A Comparison of Large-scale MOEAs with Informed Initialization for Voltage Transformer Ratio Error Estimation
• Enabling Surrogate-assisted Evolutionary Reinforcement Learning via Policy Embedding
• An Improved MPCA Algorithm with Weight Matrix Based on Many-objective Optimization
• Machine Learning & Deep Learning
• Research on Helmet Wearing Detection Based on Improved YOLOv4 Algorithm
• Research on Target Detection Algorithm of Unmanned Surface Vehicle Based on Deep Learning
• A Review On Bio-inspired Fluid Mechanics Via Deep Reinforcement Learning
• Memristor-Based Neural Network Circuit of Operant Conditioning with Overshadowing
• Continual Learning with a Memory of Non-similar Samples
• Research on Soil Moisture Prediction Based on LSTM-Transformer Model
• Graph Contrastive Learning with Intrinsic Augmentations
• Research on Global Collision Avoidance Algorithm for Unmanned Ship Based on Improved Artificial Potential Field Algorithm
• OCET: One-dimensional Convolution Embedding Transformer for Stock Trend Prediction
• A Rapid, Precise Spiking Neural Network Approach for Image Recognition
• Research on Improved Image Dehazing Algorithm Based on Dark Channel Prior
• Reinforcement Learning Based Vertical Scaling for Hybrid Deployment in Cloud Computing
• Swing-up and Balance Control of Cart-pole Based on Reinforcement Learning DDPG
• Yolov5 Outdoor Dynamic Object Detection Based on Multi-scale Feature Fusion
• Intelligent Control & Simulation
• Multi-UUV Formation Cooperative Full-area Coverage Search Method
• Multi-scale Simulations of Flow in the Upper Open Area of a Luxury Cruise Ship
• Research on Course Control Algorithm of Unmanned Craft based on Model Predictive Control
• Multi-UUV Underwater Target Cooperative Detection Task Planning and Assignment
• Multi-UUV Cooperative Navigation and Positioning Algorithm under Communication Delay
• The Research of the Consistency Control under The Condition of Time-lag of Isomerism AUV Group Communication
• Non-uniform Deformation Behavior of Magneto-sensitive Elastomer Containing Uniform Sphere Particles with V Arrangement
• Study on the Influence of Exit Width Change on Heterogeneous Passengers Evacuation based on the Social Force Model
• A Review of Longitudinal Vibration and Vibration Reduction Technology of Propulsion Shafting
• Design and Simulation of Heading Controller for Unmanned Boat Based on Fuzzy Neural PID
• Flexible Formation Control of Multiple Unmanned Vehicles based on Artificial Potential Field Method
• Local Path Planning Combined with the Motion State of Dynamic Obstacles
• Simulation of Airflow Characteristics of a Seabird Following a Ship Based on Steady States
• Numerical Simulation of Bionic Undulating Fin Surface Drag Reduction Structure
• Molecular Computing & Nanotechnology
• Integrated Design and Absorbing Performance Analysis for Periodic Wave Absorbing and Bearing Structures
• Diffusion Optimization Algorithm Based on Membrane Calculation
• Tuning Geometric Conformations of Curved DNA Structures by Controlling Positions of Nicks
• A Sensitive Nanothermometer Based on DNA Triplex Structure
• Microwave Absorption Properties of Double-layer Absorbing Material Based on Carbonyl Iron and Graphene Composites
• Reconfigurable Nanobook Structure Driven by Polymerase-triggered DNA Strand Displacement
• An Analysis for Thermal Conductivity of Graphene/polymer Nanocomposites
• Simulation of Aflatoxin B1 Detection Model Based on Hybridization Chain Reaction.

This book constitutes the refereed proceedings of the 17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022, held in Wuhan, China, during December 1618, 2022. The 56 full papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: evolutionary computation and swarm intelligence; machine learning and deep learning; intelligent control and simulation and molecular computing and nanotechnology.

• Networks and Complex systems
• Collaborative learning over Cellular Automata
• An agent-based model for crowd simulation
• Chemical Neural Networks and Semantic Information investigated through Synthetic Cells
• Spread of perturbations in supply chain networks: the effect of the bow-tie organization on the resilience of the global automotive system
• An efficient implementation of Flux Variability Analysis for metabolic networks
• Exploring the solution space of cancer evolution inference frameworks for single-cell sequencing data
• Computational investigation of the clustering of droplets in widening pipe geometries
• Network Creation During Agglomeration Processes of Polydisperse and Monodisperse Systems of Droplets
• Artificial Chemistry Performed in an Agglomeration of Droplets with Restricted Molecule Transfer
• Modelling wet-dry cycles in the binary polymer model
• On the growth of chemical diversity
• Kernel-based early fusion of structure and attribute information for detecting communities in attributed networks
• Cultural Innovation Triggers Inequality in a Sharing Economy
• Metaheuristics, robotics, and machine learning
• Online adaptation of robots controlled by nanowire networks: A preliminary study
• The role of dynamical regimes of online adaptive BN-robots in noisy environments
• A novel evolutionary approach for Neural Architecture Search
• Single and Multi-objective Genetic Programming Methods for Prediction Intervals
• Green design of Single Frequency Networks by Multiband Robustness and a hybrid metaheuristic
• WanDa: A Mobile Application to Prevent Wandering
• Magnetic Devices Behavioral Modeling based on Genetic Programming and Neural Networks
• Evolutionary Stitching of Plot Units with Character Threads
• Impact of Morphology Variations on Evolved Neural Controllers for Modular Robots
• EGSGP: an Ensemble System Based on Geometric Semantic Genetic Programming
• Real-time monitoring tool for SNN hardware architecture.

This book constitutes the refereed proceedings of the 16th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2022, held in Gaeta, Italy, during September 14-16, 2022. The 21 full papers and 3 short papers included in this book were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: answer set programming; networks and complex systems, metaheuristics, robotics, and machine learning.

• Networks
• Dynamical criticality in growing networks
• Effective Resistance based Weight Thresholding for Community Detection
• An Oracle for the Optimization of Underconstrained Compositions of Neural Networks - The Tick Hazard Use Case
• Droplets, Fluids, and Synthetic Biology
• Obstacles on the Pathway towards Chemical Programmability using Agglomerations of Droplets
• The Good, the Bad and the Ugly: droplet recognition by a "shootout"-heuristics
• Exploring the three-dimensional arrangement of droplets
• Geometric restrictions to the agglomeration of spherical particles
• Effectiveness of Dynamic Load Balancing in Parallel Execution of a Subsurface Flow Cellular Automata Model
• Two possible AI-related paths for bottom-up synthetic cell research
• Robot Systems
• A hybrid control system architecture for a mobile robot to provide an energy-efficient and fast data processing
• On the evolution of mechanisms for collective decision making in a swarm of robots
• A novel online adaptation mechanism in artificial systems provides phenotypic plasticity
• Computer Vision and Computational Creativity
• Exploration of Genetic Algorithms and CNN for Melanoma Classification
• Using Genetic Algorithms to optimize a deep learning based system for the prediction of cognitive impairments
• Autonomous inspections of power towers with an UAV
• Self-organizing Maps of Artificial Neural Classifiers - a Brain like Pin Factory
• Evolutionary Music: Statistical Learning and Novelty for automatic improvisation
• Semantic Search
• ARISE: Artificial Intelligence Semantic Search Engine
• Artificial Medicine and Pharmacy
• Influence of the Antigen Pattern Vector on the Dynamics in a Perceptron-based Artificial Immune - Tumour-Ecosystem during and after Radiation Therapy
• Two-level detection of dynamic organization in cancer evolution models
• Artificial chemical neural network for drug discovery applications
• Trade and Finance
• Information Flow Simulations in Multi-Dimensional and Dynamic Systems
• Investigation of the Ramsey-Pierce-Bowman Model
• Ethics in Computational Modelling
• Ethical Aspects of Computational Modelling in Science, Decision Support and Communication.

This book constitutes the proceedings of the 15th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2021, held in Winterthur, Switzerland, in September 2022. The 14 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 25 submissions. The papers are organized in the following topical sections: Networks; Droplets, Fluids, and Synthetic Biology; Robot Systems; Computer Vision and Computational Creativity; Semantic Search; Artificial Medicine and Pharmacy; Trade and Finance; Ethics in Computational Modelling.

• Intro; Preface; Organization; Contents; Theory; On Bi-objective Convex-Quadratic Problems; 1 Introduction; 2 Theoretical Properties of Bi-objective Convex-Quadratic Problems; 2.1 Preliminaries; 2.2 Pareto Set; 2.3 Convexity of the Pareto Front; 3 New Classes of Bi-objective Test Functions; 4 Summary; References; An Empirical Investigation of the Optimality and Monotonicity Properties of Multiobjective Archiving Methods; 1 Introduction; 2 Experimental Design; 2.1 Assessment Indexes; 2.2 Archivers Investigated; 2.3 Test Problems; 2.4 General Experimental Settings; 3 Results; 3.1 Optimal Ratio

• 3.2 Deterioration Ratio3.3 Summary; 4 Concluding Remarks; References; Evolutionary Multi-objective Optimization Using Benson's Karush-Kuhn-Tucker Proximity Measure; 1 Introduction; 2 KKT Based Proximity Measure; 3 Proposed B-KKT Proximity Measure; 4 Results; 4.1 Two-Objective Optimization Problems; 4.2 Three-Objective Optimization Problems; 4.3 Many-Objective Optimization Problems; 4.4 Engineering Design Problem; 5 Conclusions; References; On the Convergence of Decomposition Algorithms in Many-Objective Problems; 1 Introduction; 2 Numerical Experiments; 3 Interpretation of Results

• 4 ConclusionReferences; Algorithms; A New Hybrid Metaheuristic for Equality Constrained Bi-objective Optimization Problems; 1 Introduction; 2 Background; 3 Proposed Algorithm (M-NSGA-II/PT); 3.1 First Stage: Rough Approximation via Micro-NSGA-II; 3.2 Second Stage: Refinement via PT; 4 Numerical Results; 5 Conclusions and Future Work; References; Make Evolutionary Multiobjective Algorithms Scale Better with Advanced Data Structures: Van Emde Boas Tree for Non-dominated Sorting; 1 Introduction; 2 Preliminaries; 3 The Divide-and-Conquer Algorithm for Non-dominated Sorting; 3.1 The General Plan

• 3.2 Sweep Line Algorithms for m = 24 The Van Emde Boas Tree; 5 Efficient Implementation of the Van Emde Boas Tree; 6 Implementation and Analysis of the Whole Algorithm; 7 Experiments; 8 Conclusion; References; Toward a New Family of Hybrid Evolutionary Algorithms; 1 Introduction; 2 Background; 3 Subspace Polynomial Mutation Operator; 4 Multi-objective Descent Directions Within MOEAs; 4.1 Equality Constrained MOPs; 4.2 Gradient-Free Descent Direction; 5 Application: Hybrid Algorithm for Constrained Optimization; 6 Conclusions and Future Work; References

• Adjustment of Weight Vectors of Penalty-Based Boundary Intersection Method in MOEA/D1 Introduction; 2 Related Works; 3 MOEA/D-PBI with Adjusted Weight Vectors; 4 Computational Experiments; 4.1 Experimental Settings; 4.2 Experimental Results; 5 Conclusions; References; GD
• E4: The Generalized Differential Evolution with Ordered Mutation; 1 Introduction; 2 Background Review; 2.1 Generalized Differential Evolution; 2.2 Existing Single Objective Differential Evolution with Ordered Mutation; 3 Proposed Algorithm: The Generalized Differential Evolution with the Ordered Mutation (GDE4); 4 Experiment

This book constitutes the refereed proceedings of the 10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019 held in East Lansing, MI, USA, in March 2019. The 59 revised full papers were carefully reviewed and selected from 76 submissions. The papers are divided into 8 categories, each representing a key area of current interest in the EMO field today. They include theoretical developments, algorithmic developments, issues in many-objective optimization, performance metrics, knowledge extraction and surrogate-based EMO, multi-objective combinatorial problem solving, MCDM and interactive EMO methods, and applications.
(source: Nielsen Book Data)

• Plenary Talks
• Interactive Approaches in Multiple Criteria Decision Making and Evolutionary Multi-objective Optimization
• Towards Automatically Configured Multi-objective Optimizers
• A Review of Evolutionary Multiobjective Optimization Applications in Aerospace Engineering
• Performance evaluation of multiobjective optimization algorithms: quality indicators and the attainment function
• Theory and Hyper-Heuristics
• A Multimodal Approach for Evolutionary Multi-objective Optimization (MEMO): Proof-of-Principle Results
• Unwanted Feature Interactions Between the Problem and Search Operators in Evolutionary Multi-objective Optimization
• Neutral but a Winner! How Neutrality helps Multiobjective Local Search Algorithms
• To DE or not to DE? Multi-Objective Differential Evolution Revisited from a Component-Wise Perspective
• Model-Based Multi-Objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark
• Temporal Innovization: Evolution of Design Principles Using Multi-objective Optimization
• MOEA/D-HH: A Hyper-Heuristic for Multi-objective Problems
• Using hyper-heuristic to select leader and archiving methods for many-objective problems
• Algorithms
• Adaptive Reference Vector Generation for Inverse Model Based Evolutionary Multiobjective Optimization with Degenerate and Disconnected Pareto Fronts
• MOEA/PC: Multiobjective Evolutionary Algorithm Based on Polar Coordinates
• GD-MOEA: A New Multi-Objective Evolutionary Algorithm based on the Generational Distance Indicator
• Experiments on Local Search for Bi-objective Unconstrained Binary Quadratic Programming
• A Bug in the Multiobjective Optimizer IBEA: Salutary Lessons for Code Release and a Performance Re-Assessment
• A Knee-based EMO Algorithm with an Efficient Method to Update Mobile Reference Points
• A Hybrid Algorithm for Stochastic Multiobjective Programming Problem
• Parameter Tuning of MOEAs using a Bilevel Optimization Approach
• Pareto adaptive scalarising functions for decomposition based algorithms
• A bi-level multiobjective PSO algorithm
• An interactive simple indicator-based evolutionary algorithm (I-SIBEA) for multiobjective optimization problems
• Combining Non-dominance, Objective-sorted and Spread Metric to Extend Firefly Algorithm to Multi-objective Optimization
• GACO: a parallel evolutionary approach to multi-objective scheduling
• Kriging Surrogate Model Enhanced by Coordinate Transformation of Design Space Based on Eigenvalue Decomposition
• A Parallel Multi-Start NSGA II Algorithm for Multiobjective Energy Reduction Vehicle Routing Problem
• Evolutionary Inference of Attribute-based Access Control Policies
• Hybrid Dynamic Resampling for Guided Evolutionary Multi-Objective Optimization
• A Comparison of Decoding Strategies for the 0/1 Multi-objective Unit Commitment Problem
• Comparing Decomposition-based and Automatically Component-Wise Designed Multi-objective Evolutionary Algorithms
• Upper Confidence Bound (UCB) Algorithms for Adaptive Operator Selection in MOEA/D
• Towards Understanding Bilevel Multi-objective Optimization with Deterministic Lower Level Decisions.

This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimarães, Portugal in March/April 2015. The 68 revised full papers presented together with 4 plenary talks were carefully reviewed and selected from 90 submissions. The EMO 2015 aims to continue these type of developments, being the papers presented focused in: theoretical aspects, algorithms development, many-objectives optimization, robustness and optimization under uncertainty, performance indicators, multiple criteria decision making and real-world applications.

• Many-Objectives Optimization, Performance and Robustness
• Evolutionary Many-objective Optimization based on Kuhn-Munkres? Algorithm
• A KKT Proximity Measure for Evolutionary Multi-Objective and Many-Objective Optimization
• U-NSGA-III: A Unified Evolutionary Optimization Procedure for Single, Multiple, and Many Objectives? Proof-of- Principle Results
• Clustering based parallel Many-objective Evolutionary Algorithms using the shape of the objective vectors
• Faster Exact Algorithms for Computing Expected Hypervolume Improvement
• A GPU-based Algorithm for a Faster Hypervolume Contribution Computation
• A Feature-based Performance Analysis in Evolutionary Multiobjective Optimization
• Modified Distance Calculation in Generational Distance and Inverted Generational Distance
• On the Behavior of Stochastic Local Search within Parameter Dependent MOPs
• An Evolutionary Approach to Active Robust Multiobjective Optimisation
• Linear scalarization Pareto front identification in stochastic environments
• Elite Accumulative Sampling Strategies for Noisy Multi-Objective Optimisation
• Guideline Identification for Optimization under Uncertainty through the Optimization of a Boomerang Trajectory
• MCDM
• Using indifference information in robust ordinal regression
• A Multi-objective genetic algorithm for inferring inter-criteria parameters for water supply consensus
• Genetic Algorithm Approach for a Class of Multi-criteria, Multi-vehicle Planner of UAVs
• An Interactive Evolutionary Multiobjective Optimization Method: Interactive WASF-GA
• On Generalizing Lipschitz Global Methods for Multiobjective Optimization
• Dealing with scarce optimization time in complex logistics optimization: A study on the biobjective Swap-Body Inventory Routing Problem
• Machine Decision Makers as a Laboratory for Interactive EMO
• Real World Applications
• Aircraft Air Inlet Design Optimization via Surrogate-Assisted Evolutionary Computation
• Diesel Engine Drive-Cycle Optimization with the Integrated Optimization Environment? Liger
• Re-design for robustness: An approach based on many objective optimization
• A Model for a Human Decision-Maker in a Polymer Extrusion Process
• Multi-Objective Optimization of Gate Location and Processing Conditions in Injection Molding Using MOEAs: Experimental Assessment
• A Multi-Criteria Decision Support System for a Routing Problem in Waste Collection
• Application of Evolutionary Multiobjective Algorithms for solving the problem of Energy Dispatch in Hydroelectric Power Plants
• Solutions in Under 10 Seconds for Vehicle Routing Problems with Time Windows using Commodity Computers
• A comparative study of algorithms for solving the Multiobjective Open-Pit Mining Operational Planning Problems
• A Model to Select a Portfolio of Multiple Spare Parts for a Public Bus Transport Service Using NSGA II.-A Multi-Objective Optimization Approach Associated to Climate Change Analysis to Improve Systematic Conservation Planning
• Marginalization in Mexico: An Application of the Electre III[Pleaseinsertintopreamble]MOEA Methodology
• Integrating Hierarchical Clustering and Pareto-Efficacy to Preventive Controls Selection in Voltage Stability Assessment
• Multi-objective Evolutionary Algorithm with Discrete Differential Mutation Operator for Service Restoration in Largescale
• Distribution Systems
• Combining Data Mining and Evolutionary Computation for Multi-Criteria Optimization of Earthworks
• Exploration of Two-Objective Scenarios on Supervised Evolutionary Feature Selection: a Survey and a Case Study
• (Application to Music Categorisation)
• A Multi-Objective Approach for Building Hyperspectral Remote Sensed Image Classifier Combiners
• Multi-Objective Optimization of Barrier Coverage with Wireless Sensors
• Comparison of Single and Multi-objective Evolutionary Algorithms for Robust Link-state Routing.

This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015 held in Guimarães, Portugal in March/April 2015. The 68 revised full papers presented together with 4 plenary talks were carefully reviewed and selected from 90 submissions. The EMO 2015 aims to continue these type of developments, being the papers presented focused in: theoretical aspects, algorithms development, many-objectives optimization, robustness and optimization under uncertainty, performance indicators, multiple criteria decision making and real-world applications.

Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.
(source: Nielsen Book Data)

Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.
(source: Nielsen Book Data)

• Diffusion of Shapes (R S Shaw & N H Packard)
• FDC-Based Particle Swarm Optimization (A Azzini et al.)
• Predictive Neural Networks in the Design of Experiments (D De March et al.)
• Prefrontal Cortex and Action Sequences: A Review on Neural Computational Models (I Gaudiello et al.)
• Bio-Inspired ICT for Evolutionary Emotional Intelligence (M Villamira & P Cipresso)
• Cooperation in Corvids: A Simulative Study with Evolved Robots (O Miglino et al.)
• Distributed Processes in a Agent-Based Model of Innovation (L Ansaloni et al.)
• Imaginary or Actual Artificial Worlds Using a New Tool in the ABM Perspective (P Terna)
• Dynamics of Interconnected Boolean Networks with Scale-Free Topology (C Damiani et al.)
• Semi-Synthetical Minimal Cells (P Stano & P L Luisi)
• and Other Papers.
• (source: Nielsen Book Data)

The Italian community in Artificial Life and Evolutionary computation has grown remarkably in recent years, and this book is the first broad collection of its major interests and achievements (including contributions from foreign countries). The contributions in Artificial Life as well as in Evolutionary Computation allow one to see the deep connections between the two fields. The topics addressed are extremely relevant for present day research in Artificial Life and in Evolutionary Computation, which include important contributions from very well-known researchers. The volume provides a very broad picture of the Italian activities in this field.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• Applications of Evolutionary Computation
• An Enhanced Opposition-Based Evolutionary Feature Selection Approach
• 1 Introduction
• 2 Moth Flame Optimization
• 2.1 Binary Moth Flame Optimization
• 2.2 Binary Moth Flame Optimization for Feature Selection
• 3 The Proposed Approach
• 3.1 Initialization Using Opposition-Based Method
• 3.2 Retiring Flame
• 4 Experimental Setup and Results
• 5 Conclusions
• References
• A Methodology for Determining Ion Channels from Membrane Potential Neuronal Recordings
• 1 Introduction

• 2 Conductance-Based Model Description
• 3 Defining a Benchmark with Known Types of Ion Channels
• 4 Methodology and Experimental Setup
• 5 Experimental Results
• 6 Conclusions
• A Mathematical Description of the Models
• B Experimental Setup and Parameter Ranges
• References
• Swarm Optimised Few-View Binary Tomography
• 1 Introduction
• 2 Binary Tomographic Reconstruction
• 3 Swarm Optimisation
• 4 Constrained Search in High Dimensions
• 5 Reconstructions
• 6 Results
• 7 Discussion
• 8 Conclusions
• References

• Comparing Basin Hopping with Differential Evolution and Particle Swarm Optimization
• 1 Introduction
• 2 The Metaheuristics Studied
• 2.1 Basin Hopping
• 2.2 Differential Evolution
• 2.3 Particle Swarm Optimization
• 3 The Benchmarking Environment
• 4 Experimental Setup
• 5 Experimental Results
• 6 Conclusions
• References
• Combining the Properties of Random Forest with Grammatical Evolution to Construct Ensemble Models
• 1 Introduction
• 2 Methodology
• 2.1 Structured Grammatical Evolution
• 2.2 Random Structured Grammatical Evolution for Symbolic Regression Problems

• 3 Experimental Setup
• 3.1 Study Problems
• 3.2 Configuration of the Algorithms
• 4 Results
• 5 Conclusions
• References
• EvoCC: An Open-Source Classification-Based Nature-Inspired Optimization Clustering Framework in Python
• 1 Introduction
• 2 Related Works
• 3 Methodology
• 4 Framework Overview
• 4.1 Parameters
• 4.2 Datasets
• 4.3 Clustering with EvoCluster
• 4.4 Classification
• 4.5 Evaluation Measures
• 4.6 Results Management
• 5 Experiments and Visualizations
• 6 Conclusion and Future Works
• References
• Evolution of Acoustic Logic Gates in Granular Metamaterials

• 1 Introduction
• 2 Problem Statement
• 3 Simulation Setup
• 3.1 2D Granular Simulator
• 3.2 Optimization Method
• 4 Results and Discussion
• 4.1 Evolution of an Acoustic Band Gap
• 4.2 Evolving an AND Gate
• 4.3 Evolving an XOR Gate
• 5 Conclusion and Future Work
• References
• Public-Private Partnership: Evolutionary Algorithms as a Solution to Information Asymmetry
• 1 Introduction
• 2 The Problem
• 3 Proposed Approach
• 3.1 The Model
• 3.2 Data
• 3.3 Adversarial Optimization
• 3.4 Operator (EA1)
• 3.5 Public Administration (EA2)
• 4 Experimental Evaluation

This book constitutes the refereed proceedings of the 25th International Conference on Applications of Evolutionary Computation, EvoApplications 2022, held as part of Evo*2022, in April 2022, co-located with the Evo*2022 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented in this book were carefully reviewed and selected from 67 submissions. .
(source: Nielsen Book Data)

• On Restricting Real-Valued Genotypes in Evolutionary Algorithms.- Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions.- Co-Optimising Robot Morphology and Controller in a Simulated Open-ended Environment.- Multi-objective workforce allocation in construction projects.- Generating Duplex Routes for Robust Bus Transport Network by Improved Multi-objective Evolutionary Algorithm based on Decomposition.- Combining Multi-objective Evolutionary Algorithms with deep generative models towards focused molecular design.- A Multi-Objective Evolutionary Algorithm Approach for Optimizing Part Quality Aware Assembly Job Shop Scheduling Problems.- Evolutionary Grain-Mixing to Improve Profitability in Farming Winter Wheat.- Automatic Modular Design of Behavior Trees for Robot Swarms with Communication Capabilites.- Salp Swarm Optimization Search Based Feature Selection for Enhanced Phishing Websites Detection.- Real Time Optimisation of Traffic Signals to Prioritise Public Transport.- Adaptive Covariance Pattern Search.- Evaluating the Success-History based Adaptive Differential Evolution in the Protein Structure Prediction problem.- Beyond Body Shape and Brain: Evolving the Sensory Apparatus of Voxel-based Soft Robots.- Desirable Objective Ranges in Preference-based Evolutionary Multiobjective Optimization.- Improving Search Efficiency and Diversity of Solutions in Multiobjective Binary Optimization by Using Metaheuristics plus Integer Linear Programming.- Automated, Explainable Rule Extraction from MAP-Elites archives.- EDM-DRL: Toward Stable Reinforcement Learning through Ensembled Directed Mutation.- Continuous Ant-Based Neural Topology.- Playing with Dynamic Systems - Battling Swarms in Virtual Reality.- EvoCraft: A New Challenge for Open-Endedness.- A Profile-Based 'GrEvolutionary' Hearthstone Agent.- Modelling Asthma Patients' Responsiveness to Treatment Using Feature Selection and Evolutionary Computation.- Bayesian Networks for Mood Prediction Using Unobtrusive Ecological Momentary Assessments.- A Multi-Objective Multi-Type Facility Location Problem for the Delivery of Personalised Medicine.- RDE-OP: A Region-Based Differential Evolution Algorithm Incorporation Opposition-Based Learning for Optimising the Learning Process of Multi-Layer Neural Networks.- Estimation of Grain-level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 using Genetic Programming.- EDA-based optimization of blow-off valve positions for centrifugal compressor systems.- 3D-2D Registration using X-ray Simulation and CMA-ES.- Lateralized Approach for Robustness AgainstAttacks in Emotion Categorization from Images.- Improved Crowding Distance in Multi-objective Optimization for Feature Selection in Classification.- Deep Optimisation: Multi-Scale Evolution by Inducing and Searching in Deep Representations.- Evolutionary Planning in Latent Space.- Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning.- Effective Universal Unrestricted Adversarial Attacks using a MOE Approach.- Improving Distributed Neuroevolution Using Island Extinction and Repopulation.- An Experimental Study of Weight Initialization and Lamarckian Inheritance on Neuroevolution.- Towards Feature-Based Performance Regression Using Trajectory Data.- Demonstrating the Evolution of GANs through t-SNE.- Optimising diversity in classifier ensembles of classification trees.- WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets.- Evolving Character-Level DenseNet Architectures using Genetic Programming.- Transfer Learning for Automated Test Case Prioritization using XCSF.- On the Effects of Absumption for XCS with Continuous-Valued Inputs.- A NEAT Visualisation of Neuroevolution Trajectories.- Evaluating Models with Dynamic Sampling Holdout.- Event-driven multi-algorithm optimization: mixing Swarm and Evolutionary strategies.- TensorGP - Genetic Programming Engine in TensorFlow.- A novel evolutionary approach for IoT-based water contaminant detection.- Evolutionary Algorithms for Roughness Coefficient Estimation in River Flow Analyses.- EA-based ASV Trajectory Planner for Pollution Detection in Lentic Waters.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 24th International Conference on Applications of Evolutionary Computation, EvoApplications 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events EuroGP, EvoCOP, and EvoMUSART. The 51 revised full papers presented in this book were carefully reviewed and selected from 78 submissions. The papers cover a wide spectrum of topics, ranging from applications of evolutionary computation; applications of deep bioinspired algorithms; soft computing applied to games; machine learning and AI in digital healthcare and personalized medicine; evolutionary computation in image analysis, signal processing and pattern recognition; evolutionary machine learning; parallel and distributed systems; and applications of nature inspired computing for sustainability and development. .
(source: Nielsen Book Data)