Applications of Evolutionary Computation
Springer International Publishing (Verlag)
978-3-319-31152-4 (ISBN)
Thetwo volumes LNCS 9597 and 9598 constitute the refereed conference proceedingsof the 19th European Conference on the Applications of Evolutionary Computation,EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-locatedwith the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART.
The57 revised full papers presented together with 17 poster papers were carefullyreviewed and selected from 115 submissions. EvoApplications 2016 consisted ofthe following 13 tracks: EvoBAFIN (natural computing methods in businessanalytics and finance), EvoBIO (evolutionary computation, machine learning anddata mining in computational biology), EvoCOMNET (nature-inspired techniquesfor telecommunication networks and other parallel and distributed systems),EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY(evolutionary computation in energy applications), EvoGAMES (bio-inspiredalgorithms in games), EvoIASP (evolutionary computation in image analysis,signal processing, and pattern recognition), EvoINDUSTRY (nature-inspiredtechniques in industrial settings), EvoNUM (bio-inspired algorithms forcontinuous parameter optimization), EvoPAR (parallel implementation ofevolutionary algorithms), EvoRISK (computational intelligence for riskmanagement, security and defence applications), EvoROBOT (evolutionaryrobotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamicenvironments).EvoNUM: Local Fitness Meta-Models with Nearest Neighbor Regression.- Validatingthe Grid Diversity Operator: an Infusion Technique for Diversity Maintenance inPopulation-Based Optimisation Algorithms.- Benchmarking Languages for EvolutionaryAlgorithms.- On the Closest Averaged Hausdorff Archive for a Circularly ConvexPareto Front.- Evolving Smoothing Kernels for Global Optimization.- EvoPAR: ImplementingParallel Differential Evolution on Spark.- ECJ+HADOOP: An Easy Way to Deploy MassiveRuns of Evolutionary Algorithm.- Addressing High Dimensional Multi-Objective OptimizationProblems by Coevolutionary Islands with Overlapping Search Spaces.- CompilablePhenotypes: 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: LeveragingOnline Racing and Population Cloning in Evolutionary Multirobot Systems.- Multi-AgentBehavior-Based Policy Transfer.- On-line Evolution of Foraging Behaviour in aPopulation of Real Robots.- Hybrid Control for a Real Swarm Robotics System inan Intruder Detection Task.- EvoSTOC: Direct Memory Schemes for Population-BasedIncremental Learning in Cyclically Changing Environments.- Simheuristics forthe Multiobjective Nondeterministic Firefighter Problem in a Time-ConstrainedSetting.- Benchmarking Dynamic Three-Dimensional Bin Packing Problems Using Discrete-EventSimulation.- Genetic Programming Algorithms for Dynamic Environments.- AMemory-Based NSGA-II Algorithm for Dynamic Multi-Objective OptimizationProblems.- Hybrid Dynamic Resampling Algorithms for EvolutionaryMulti-objective Optimization of Invariant-Noise Problems.
| Erscheinungsdatum | 08.10.2016 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science | Theoretical Computer Science and General Issues |
| Zusatzinfo | XXVI, 329 p. 94 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | Algorithm analysis and problem complexity • Applications • Artificial Intelligence • bioinspired methods • Biologically Inspired Computing • combinatorial optimization • Communication Networks • Complex Systems • Computer Games • Computer Science • conference proceedings • Data Mining • Distributed Systems • Energy applications • evolutionary algorithms • evolutionary computation • Feature Selection • finance and economics • Genetic algorithms • genetic programming • Informatics • machine learning • Natural Computing • Particle swarm optimization • Problem Solving • Research |
| ISBN-10 | 3-319-31152-2 / 3319311522 |
| ISBN-13 | 978-3-319-31152-4 / 9783319311524 |
| Zustand | Neuware |
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