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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.
(source: Nielsen Book Data)