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• EvoBAFIN: Enhanced Multiobjective Population-Based Incremental Learning with Applications in Risk Treaty Optimization
• Genetic Programming with Memory for Financial Trading
• Improving Fitness Functions in Genetic Programming for Classification on Unbalanced Credit Card Data
• Evolving Classification Models for Prediction of Patient Recruitment in Multicentre Clinical Trials Using Grammatical Evolution
• Portfolio Optimization, a Decision-Support Methodology for Small Budgets
• Evolutionary Multiobjective Optimization for Portfolios in Emerging Markets: Contrasting Higher Moments and Median Models
• EvoBIO: On Combinatorial Optimisation in Analysis of Protein-Protein Interaction and Protein Folding Networks
• A Multi-objective Genetic Programming Biomarker Detection Approach in Mass Spectrometry Data
• Automating Biomedical Data Science Through Tree-Based Pipeline Optimization
• Bicliques in Graphs with Correlated Edges: From Artificial to Biological Networks
• Hybrid Biclustering Algorithms for Data Mining
• Discovering Potential Clinical Profiles of Multiple Sclerosis from Clinical and Pathological Free Text Data with Constraint Non-negative Matrix Factorization
• Application of Evolutionary Algorithms for the Optimization of Genetic Regulatory Networks
• EvoCOMNET: A Hybrid Discrete Artificial Bee Colony Algorithm for the Multicast Routing Problem
• Evolving Coverage Optimisation Functions for Heterogeneous Networks Using Grammatical Genetic Programming
• Joint Topology Optimization, Power Control and Spectrum Allocation for Intra-Vehicular Multi-hop Sensor Networks Using Dandelion-Encoded Heuristics
• A Heuristic Crossover Enhanced Evolutionary Algorithm for Clustering Wireless Sensor Network
• A Variable Local Search Based Memetic Algorithm for the Load Balancing Problem in Cloud Computing
• An (MI)LP-Based Primal Heuristic for 3-Architecture Connected Facility Location in Urban Access Network Design
• Reducing Efficiency of Connectivity-Splitting Attack on Newscast via Limited Gossip
• A Distributed Intrusion Detection Framework Based on Evolved Specialized Ensembles of Classifiers
• UAV Fleet Mobility Model with Multiple Pheromones for Tracking Moving Observation Targets
• EvoCOMPLEX: Towards Intelligent Biological Control: Controlling Boolean Networks with Boolean Networks
• The Emergence of Cooperation in Public Goods Games on Randomly Growing Dynamic Networks
• Influence Maximization in Social Networks with Genetic Algorithms
• Measuring Diversity of Socio-Cognitively Inspired ACO Search
• Multiwinner Voting in Genetic Algorithms for Solving Ill-Posed Global Optimization Problems
• EvoENERGY: A Decentralized PSO with Decoder for Scheduling Distributed Electricity Generation
• Comparison of Multi-objective Evolutionary Optimization in Smart Building Scenarios
• Stigmergy-Based Scheduling of Flexible Loads
• Electrical Load Pattern Shape Clustering Using Ant Colony Optimization
• Optimization of Operation and Control Strategies for Battery Energy Storage Systems by Evolutionary Algorithms
• EvoGAMES: Orthogonally Evolved AI to Improve Difficulty Adjustment in Video Games
• There Can Be only One: Evolving RTS Bots via Joust Selection
• Constrained Level Generation through Grammar-Based Evolutionary Algorithms
• Evolving Chess-Like Games Using Relative Algorithm Performance Profiles
• Online Evolution for Multi-action Adversarial Games
• The Story of Their Lives: Massive Procedural Generation of Heroes' Journeys Using Evolved Agent-Based Models and Logical Reasoning
• Dangerousness Metric for Gene Regulated Car Driving
• Using Isovists to Evolve Terrains with Gameplay Elements
• A Spatially-Structured PCG Method for Content Diversity in a Physics-Based simulation Game
• Design and Evaluation of an Extended Learning Classifier-Based StarCraft Micro AI
• EvoIASP: A Wrapper Feature Selection Approach to Classification with Missing Data
• Bare-Bone Particle Swarm Optimisation for Simultaneously Discretising and Selecting Features For High-Dimensional Classification
• Mutual Information Estimation for Filter Based Feature Selection Using Particle Swarm Optimization
• Speaker Verification on Unbalanced Data with Genetic Programming
• Binary Tomography Reconstruction by Particle Aggregation
• Population Based Ant Colony Optimization for Reconstructing ECG Signals
• EvoINDUSTRY: Can Evolutionary Algorithms Beat Dynamic Programming for Hybrid
• NSGA-II Based Auto-Calibration of Automatic Number Plate Recognition Camera for Vehicle Speed Measurement
• Environment-Model Based Testing with Differential Evolution in an Industrial Setting
• Workforce Scheduling in Inbound Customer Call Centres with a Case Study.

The two volumes LNCS 9597 and 9598 constitute the refereed conference proceedings of the 19th European Conference on the Applications of Evolutionary Computation, EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 57 revised full papers presented together with 17 poster papers were carefully reviewed and selected from 115 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

• EvoNUM: Local Fitness Meta-Models with Nearest Neighbor Regression
• Validating the Grid Diversity Operator: an Infusion Technique for Diversity Maintenance in Population-Based Optimisation Algorithms
• Benchmarking Languages for Evolutionary Algorithms
• On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front
• Evolving Smoothing Kernels for Global Optimization
• EvoPAR: Implementing Parallel Differential Evolution on Spark
• ECJ+HADOOP: An Easy Way to Deploy Massive Runs of Evolutionary Algorithm
• Addressing High Dimensional Multi-Objective Optimization Problems by Coevolutionary Islands with Overlapping Search Spaces
• Compilable Phenotypes: Accelerating the Evaluation of Individuals in Grammatical Evolution
• GPU Accelerated Molecular Docking Simulation with Genetic Algorithms
• EvoRISK: Challenging Anti-virus Through Evolutionary Malware Obfuscation
• EvoROBOT: Leveraging Online Racing and Population Cloning in Evolutionary Multirobot Systems
• Multi-Agent Behavior-Based Policy Transfer
• On-line Evolution of Foraging Behaviour in a Population of Real Robots
• Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task
• EvoSTOC: Direct Memory Schemes for Population-Based Incremental Learning in Cyclically Changing Environments
• Simheuristics for the Multiobjective Nondeterministic Firefighter Problem in a Time-Constrained Setting
• Benchmarking Dynamic Three-Dimensional Bin Packing Problems Using Discrete-Event Simulation
• Genetic Programming Algorithms for Dynamic Environments
• A Memory-Based NSGA-II Algorithm for Dynamic Multi-Objective Optimization Problems
• Hybrid Dynamic Resampling Algorithms for Evolutionary Multi-objective Optimization of Invariant-Noise Problems.

The two volumes LNCS 9597 and 9598 constitute the refereed conference proceedings of the 19th European Conference on the Applications of Evolutionary Computation, EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 57 revised full papers presented together with 17 poster papers were carefully reviewed and selected from 115 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

• Introduction.- Resources.- Automatic software verification.- Post-silicon speed-path analysis in modern microprocessors through genetic programming.- Antenna array synthesis with Evolutionary Algorithms.- Drift correction of chemical sensors.- Development of on-line test sets for microprocessors.- Uncovering path delay faults with Multi-Objective EAs.- Software-Based Self Testing of system peripherals.- Software-based self-testing on microprocessors.
• (source: Nielsen Book Data)

"Industrial applications of evolutionary algorithms" is intended as a resource for both experienced users of evolutionary algorithms and researchers that are beginning to approach these fascinating optimization techniques. Experienced users will find interesting details of real-world problems, advice on solving issues related to fitness computation or modeling, and suggestions on how to set the appropriate parameters to reach optimal solutions. Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of several classes of evolutionary algorithms exploited to solve different problems. Inside, scholars will find useful examples on how to fill the gap between purely theoretical examples and industrial problems. The collection of case studies presented is also extremely appealing for anyone interested in Evolutionary Computation, but without direct access to extensive technical literature on the subject. After the introduction, each chapter in the book presents a test case, and is organized so that it can be read independently from the rest: all the information needed to understand the problem and the approach is reported in each part. Chapters are grouped by three themes of particular interest for real-world applications, namely prototype-based validation, reliability and test generation. The authors hope that this volume will help to expose the flexibility and efficiency of evolutionary techniques, encouraging more companies to adopt them; and that, most of all, you will enjoy your reading.
(source: Nielsen Book Data)

• Foreword.- Summary.- Introduction.- Evolutionary computation: a quick resume.- The A GP approach. - Internal representation.- Evolutionary operators.- Performance-directed features.- Configuring an evolutionary run.- Syntax of the external constraints.- Writing a compliant evaluator.- Implementation details.- Examples and applications.- Conclusions.- References.- Index.
• (source: Nielsen Book Data)

"Evolutionary Optimization: The A GP Toolkit" offers a cohesive, thorough exploration of the scattered material on A GP features that has been presented to and validated by the scientific community, giving a fresh perspective on the subject. The book begins with an overview of the most popular techniques of evolutionary computation, followed by a discussion of the theoretical and practical aspects of A GP. The design and implementation of the tool are described, providing the reader with a conceptual model of the approach and a reference for operation. Several examples are detailed, starting from the informal description of the target problem, proceeding to the writing of syntactic constraints and configuration and to fitness evaluation, ending with actual results. Practitioners, researchers and students will find this volume a valuable reference in working with A GP, whether for the resolution of real-world problems, or for testing theoretical ideas.
(source: Nielsen Book Data)

• Evolutionary computation, machine learning and data mining in computational biology
• Nature-inspired techniques for telecommunication networks and other parallel and distributed systems
• Evolutionary algorithms and complex systems
• Evolutionary computation in energy applications
• Evolutionary and natural computation in finance and economics
• Bio-inspired algorithms in games
• Evolutionary computation in image analysis, signal processing, and pattern recognition
• Nature-inspired techniques in industrial settings
• Bio-inspired algorithms for continuous parameter optimization
• Parallel implementation of evolutionary algorithms
• Computational intelligence for risk management, security and defence applications
• Evolutionary computation in robotics
• Evolutionary algorithms in stochastic and dynamic environments.

This book constitutes the refereed conference proceedings of the 18th International Conference on the Applications of Evolutionary Computation, EvoApplications 2015, held in Copenhagen, Spain, in April 2015, colocated with the Evo 2015 events EuroGP, EvoCOP, and EvoMUSART. The 72 revised full papers presented were carefully reviewed and selected from 125 submissions. EvoApplications 2015 consisted of the following 13 tracks: EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary computation in robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

• EvoSET: Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines.- On the Use of Smelly Examples to Detect Code Smells in JavaScript.- Deep Parameter Tuning of Concurrent Divide and Conquer Algorithms in Akka.- Focusing Learning-based Testing away from Known Weaknesses.- Polytypic Genetic Programming.- Evolving Rules for Action Selection in Automated Testing via Genetic Programming - A First Approach.- EvoSTOC: A New Multi-swarm Particle Swarm Optimization for Robust Optimization over Time.- The Static and Stochastic VRP with Time Windows and Both Random Customers and Reveal Times.- Pre-Scheduled Colony Size Variation in Dynamic Environments.- An Online Packing Heuristic for the Three-dimensional Container Loading Problem in Dynamic Environments and the Physical Internet.- Advancing Dynamic Evolutionary Optimization Using In-Memory Database Technology.- Road Traffic Rules Synthesis Using Grammatical Evolution.- Solving Dynamic Graph Coloring Problem Using Dynamic Pool Based Evolutionary Algorithm.- General: Meta-Heuristics for Improved RF Emitter Localization.- Automated Design of Genetic Programming Classification Algorithms Using a Genetic Algorithm.
• (source: Nielsen Book Data)

The two volumes LNCS 10199 and 10200 constitute the refereed conference proceedings of the 20th European Conference on the Applications of Evolutionary Computation, EvoApplications 2017, held in Amsterdam, The Netherlands, in April 2017, colocated with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented together with 26 poster papers were carefully reviewed and selected from 108 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoKNOW (knowledge incorporation in evolutionary computation), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoROBOT (evolutionary robotics), EvoSET (nature-inspired algorithms in software engineering and testing), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments). .
(source: Nielsen Book Data)

• EvoSET: Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines.- On the Use of Smelly Examples to Detect Code Smells in JavaScript.- Deep Parameter Tuning of Concurrent Divide and Conquer Algorithms in Akka.- Focusing Learning-based Testing away from Known Weaknesses.- Polytypic Genetic Programming.- Evolving Rules for Action Selection in Automated Testing via Genetic Programming - A First Approach.- EvoSTOC: A New Multi-swarm Particle Swarm Optimization for Robust Optimization over Time.- The Static and Stochastic VRP with Time Windows and Both Random Customers and Reveal Times.- Pre-Scheduled Colony Size Variation in Dynamic Environments.- An Online Packing Heuristic for the Three-dimensional Container Loading Problem in Dynamic Environments and the Physical Internet.- Advancing Dynamic Evolutionary Optimization Using In-Memory Database Technology.- Road Traffic Rules Synthesis Using Grammatical Evolution.- Solving Dynamic Graph Coloring Problem Using Dynamic Pool Based Evolutionary Algorithm.- General: Meta-Heuristics for Improved RF Emitter Localization.- Automated Design of Genetic Programming Classification Algorithms Using a Genetic Algorithm.
• (source: Nielsen Book Data)

The two volumes LNCS 10199 and 10200 constitute the refereed conference proceedings of the 20th European Conference on the Applications of Evolutionary Computation, EvoApplications 2017, held in Amsterdam, The Netherlands, in April 2017, colocated with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented together with 26 poster papers were carefully reviewed and selected from 108 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoKNOW (knowledge incorporation in evolutionary computation), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoROBOT (evolutionary robotics), EvoSET (nature-inspired algorithms in software engineering and testing), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments). .
(source: Nielsen Book Data)