Applications of Evolutionary Computation
19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings, Part II
Published on 3. April 2016
Book
Paperback/Softback
XXVI, 329 pages
978-3-319-31152-4 (ISBN)
Description
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).More details
Series
Edition
1st ed. 2016
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
94 s/w Abbildungen
XXVI, 329 p. 94 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 20 mm
Weight
540 gr
ISBN-13
978-3-319-31152-4 (9783319311524)
DOI
10.1007/978-3-319-31153-1
Schweitzer Classification
Other editions
Additional editions
Giovanni Squillero | Paolo Burelli
Applications of Evolutionary Computation
19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings, Part II
E-Book
03/2016
Springer
€53.49
Available for download
Content
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.