Metaheuristics for Multiobjective Optimisation (Lecture Notes in Economics and Mathematical Systems Vol.535) (2004. X, 249 p. w. 115 ill.)

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Metaheuristics for Multiobjective Optimisation (Lecture Notes in Economics and Mathematical Systems Vol.535) (2004. X, 249 p. w. 115 ill.)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 249 p.
  • 商品コード 9783540206378

基本説明

Contents: An Introduction to multiobjective metaheuristics for Scheduling and Timetabling/ A Genetic Algorithm for Tackling Multi-Objective Job-Shop Scheduling Problems/ etc.

Description


(Text)
A large number of real-life optimisation problems can only be realistically modelled with several‾often conflicting‾objectives. This fact requires us to abandon the concept of "optimal solution" in favour of vector optimization notions dealing with "efficient solution" and "efficient set". To solve these challenging multiobjective problems, the metaheuristics community has put forward a number of techniques commonly referred to as multiobjective meta heuristics (MOMH). By its very nature, the field of MOMH covers a large research area both in terms of the types of problems solved and the techniques used to solve these problems. Its theoretical interest and practical applicability have attracted a large number of researchers and generated numerous papers, books and spe cial issues. Moreover, several conferences and workshops have been organised, often specialising in specific sub-areas such as multiobjective evolutionary op timisation. The main purpose of this volume is to providean overview of the current state-of-the-art in the research field of MOMH. This overview is necessar ily non-exhaustive, and contains both methodological and problem-oriented contributions, and applications of both population-based and neighbourhood based heuristics. This volume originated from the workshop on multiobjective metaheuristics that was organised at the Carre des Sciences in Paris on November 4-5, 2002. This meeting was a joint effort of two working groups: ED jME and PM20.
(Table of content)
I Methodology.- A Tutorial on Evolutionary Multiobjective Optimization.- 2 Bounded Pareto Archiving: Theory and Practice.- 3 Evaluation of Multiple Objective Metaheuristics.- 4 An Introduction to Multiobjective Metaheuristics for Scheduling and Timetabling.- II Problem-oriented Contributions.- 5 A Particular Multiobjective Vehicle Routing Problem Solved by Simulated Annealing.- 6 A Dynasearch Neighborhood for the Bicriteria Traveling Salesman Problem.- 7 Pareto Local Optimum Sets in the Biobjective Traveling Salesman Problem: An Experimental Study.- 8 A Genetic Algorithm for Tackling Multiobjective Job-shop Scheduling Problems.- 9 RPSGAe - Reduced Pareto Set Genetic Algorithm: Application to Polymer Extrusion.

Table of Contents

Part I Methodology
1 A Tutorial on Evolutionary Multiobjective
Optimization
Eckart Zitzler, Marco Laumanns, Stefan 3 (36)
Bleuler
2 Bounded Pareto Archiving: Theory and
Practice
Joshua Knowles, David Corne 39 (26)
3 Evaluation of Multiple Objective
Metaheuristics
Andrzej Jaszkiewicz 65 (26)
4 An Introduction to Multiobjective
Metaheuristics for Scheduling and Timetabling
J. Dario Landa Silva, Edmund K. Burke, 91 (42)
Sanja Petrovic
Part II Problem-oriented Contributions
5 A Particular Multiobjective Vehicle Routing
Problem Solved by Simulated Annealing
Daniel Tuyttens, Jacques Teghem, Nasser 133(20)
El-Sherbeny
6 A Dynasearch Neighborhood for the
Bicriteria Traveling Salesman Problem
Eric Angel, Evripidis Bampis, Laurent 153(24)
Gourv駸
7 Pareto Local Optimum Sets in the
Biobjective Traveling Salesman Problem: An
Experimental Study
Luis Paquete, Marco Chiarandini, Thomas 177(24)
St zle
8 A Genetic Algorithm for Tackling
Multiobjective Job-shop Scheduling Problems
Joost Garen 201(20)
9 RPSGAe - Reduced Pareto Set Genetic
Algorithm: Application to Polymer Extrusion
Ant io Gaspar-Cunha, Jos A. Covas 221