Nature inspired cooperative strategies for optimization (NICSO 2008)

The inspiration from Biology and the Natural Evolution process has become a research area within computer science. For instance, the description of the artificial 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 fittest; similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The first 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 contributions include nature-inspiredtechniques like Genetic Algorithms, Ant Colonies, Amorphous Computing, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc." Presents latest results in nature inspired cooperative strategies for optimization INDICE: From the contents: Exploration in Stochastic Algorithms: An Application on MAX–MIN Ant .- Sensitive Ants: Inducing Diversity in the Colony.- Decentralised Communication and Connectivity in Ant Trail Networks.- Detection ofnon-structured roads using visible and infrared images and an Ant Colony Optimization algorithm.- A Nature Inspired Approach for the Uncapacitated Plant Cycle Location Problem.- Particle Swarm Topologies for Resource Constrained Project Scheduling.- Discrete Particle Swarm Optimization Algorithm for Data Clustering.- A Simple Distributed Particle Swarm Optimization for Dynamic and NoisyEnvironments.- Exploring Feasible and Infeasible Regions in the Vehicle Routing Problem with Time Windows Using a Multi-Objective Particle Swarm Optimization Approach.- Two-Swarm PSO for Competitive Location Problems.- Aerodynamic Wing Optimisation Using SOMA Evolutionary Algorithm.- Experimental Analysis of aVariable Size Mono-Population Cooperative-Coevolution Strategy.- Genetic Algorithm for Tardiness Minimization in Flowshop with Blocking.- An Interactive Simulated Annealing Multi-agents Platform to Solve Hierarchical Scheduling Problems with Goals.

• ISBN: 978-3-642-03210-3
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 350
• Fecha Publicación: 01/09/2009
• Nº Volúmenes: 1
• Idioma: Inglés