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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.
(source: Nielsen Book Data)

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.
(source: Nielsen Book Data)

• 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.
• (source: Nielsen Book Data)

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)

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.
(source: Nielsen Book Data)

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.
(source: Nielsen Book Data)

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.
(source: Nielsen Book Data)

• 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.
(source: Nielsen Book Data)

• 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.
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• 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)