Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications

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Andrew Lewis, Sanaz Mostaghim, Marcus Randall
Springer Science & Business Media, May 25, 2009 - Mathematics - 360 pages
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This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences on e-Science, Grid Computing and Evolutionary computation.

 

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Contents

Evolutions Niche in MultiCriterion Problem Solving
1
Applications of Parallel Platforms and Models in Evolutionary MultiObjective Optimization
22
Asynchronous MultiObjective Optimisation in Unreliable Distributed Environments
51
Dynamic Problems and Nature Inspired Metaheuristics
79
Relaxation Labelling Using Distributed Neural Networks
110
Extremal Optimisation for Assignment Type Problems
139
Niching for Ant Colony Optimisation
165
Using Ant Colony Optimisation to Construct MeanderLine RFID Antennas
189
Benchmarking and StateoftheArt Solvers
219
Strategies for Decentralised Balancing Power
261
An Analysis of Dynamic Mutation Operators for Conformational Sampling
290
Evolving Computer Chinese Chess Using Guided Learning
325
Author Index
355
Subject Index
356
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