Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)

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Natalio Krasnogor, Belén Melián-Batista, José Andrés Moreno-Pérez, J. Marcos Moreno-Vega, David Alejandro Pelta
Springer Science & Business Media, Sep 14, 2009 - Technology & Engineering - 300 pages
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The inspiration from Biology and the Natural Evolution process has become a research area within computer science. For instance, the description of the arti?cial neuron given by McCulloch and Pitts was inspired from biological observations of neural mechanisms; the power of evolution in nature in the diverse species that make up our world has been related to a particular form of problem solving based on the idea of survival of the ?ttest; similarly, - ti?cial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The ?rst and second editions of the International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), were held in Granada, Spain, 2006, and in Acireale, Italy, 2007, respectively. As in these two previous editions, the aim of NICSO 2008, held in Tenerife, Spain, was to provide a forum were the latest ideas and state of the art research related to nature inspired cooperative strategies for problem solving were discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributionsincludenature-inspiredtechniqueslikeGeneticAlgorithms,Ant Colonies, Amorphous Computing, Arti?cial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.
 

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Contents

An Application on MAXMIN Ant System
1
Inducing Diversity in the Colony
14
Decentralised Communication and Connectivity in Ant Trail Networks
25
Detection of Nonstructured Roads Using Visible and Infrared Images and an Ant Colony Optimization Algorithm
37
A Nature Inspired Approach for the Uncapacitated Plant Cycle Location Problem
49
Particle Swarm Topologies for Resource Constrained Project Scheduling
61
Discrete Particle Swarm Optimization Algorithm for Data Clustering
74
A Simple Distributed Particle Swarm Optimization for Dynamic and Noisy Environments
89
Landscape Mapping by Multipopulation Genetic Algorithm
165
An Interactive Simulated Annealing Multiagents Platform to Solve Hierarchical Scheduling Problems with Goals
177
Genetic Algorithm and Advanced Tournament Selection Concept
189
TerrainBased Memetic Algorithms for Vector Quantizer Design
197
Cooperating Classifiers
212
Evolutionary Multimodal Optimization for Nash Equilibria Detection
227
On the Computational Properties of the MultiObjective Neural Estimation of Distribution Algorithm
238
Optimal Time Delay in the Control of Epidemic
253

Exploring Feasible and Infeasible Regions in the Vehicle Routing Problem with TimeWindows Using a Multiobjective Particle Swarm Optimization ...
103
TwoSwarm PSO for Competitive Location Problems
115
AerodynamicWing Optimisation Using SOMA Evolutionary Algorithm
127
Experimental Analysis of a Variable Size Monopopulation CooperativeCoevolution Strategy
139
Genetic Algorithm for Tardiness Minimization in Flowshop with Blocking
153
Parallel HypervolumeGuided Hyperheuristic for Adapting the Multiobjective Evolutionary Island Model
261
A Cooperative Strategy for Guiding the Corridor Method
273
On the Performance of Homogeneous and Heterogeneous Cooperative Search Strategies
287
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