Advances in Multi-Objective Nature Inspired Computing

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Carlos Coello Coello, Clarisse Dhaenens, Laetitia Jourdan
Springer Science & Business Media, Feb 4, 2010 - Mathematics - 195 pages
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The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.

 

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Contents

Problematic and Context
1
Approximating ParetoOptimal Sets Using Diversity Strategies in Evolutionary MultiObjective Optimization
23
On the Velocity Update in MultiObjective Particle Swarm Optimizers
45
Approaching Dynamic MultiObjective Optimization Problems by Using Parallel Evolutionary Algorithms
63
A Software Framework for Evolutionary MultiObjective Optimization
87
A Survey and a New Approach
118
On the Performance of Local Search for the Biobjective Traveling Salesman Problem
143
A Biobjective Metaheuristic for Disaster Relief Operation Planning
166
Author Index
188
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