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Expériences with Stochastic Algorithms fir a class of Constrained Global Optimisation Problems

Published online by Cambridge University Press:  15 August 2002

Abdellah Salhi ,
L.G. Proll ,
D. Rios Insua  and
J.I. Martin
Abdellah Salhi
Affiliation:
Department of Mathematics, University of Essex,Wivenhoe Park, Colchester CO4 3SQ, U.K.
L.G. Proll
Affiliation:
Scheduling and Constraint Management Group, School of Computer Studies, University of Leeds, Leeds LS2 9JT, U.K.
D. Rios Insua
Affiliation:
Dipartimento de Inteligencia Artificial, Universidad Politecnica de Madrid, 28660-Madrid, Spain.
J.I. Martin
Affiliation:
Dipartimento de Inteligencia Artificial, Universidad Politecnica de Madrid, 28660-Madrid, Spain.
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Abstract

The solution of a variety of classes of globaloptimisation problemsis required in theimplementation of a framework for sensitivity analysis in multicriteria decision analysis. These problems have linear constraints, some of which have a particularstructure, anda variety of objective functions, which may be smooth or non-smooth. Thecontext in which theyarise implies a need for a single, robust solution method.The literature contains few experimental results relevant to such aneed.We report on our experience with the implementation of threestochastic algorithms for global optimisation: the multi-level singlelinkage algorithm,the topographical algorithm and the simulated annealing algorithm.Issues relating to their implementation and use to solve practicalproblems are discussed. Computational results suggest that, for the class of problems considered, simulated annealing performs well.

Keywords

Global optimisationstochastic methodsconstraintsmultistartsimulated annealing.
Type
Research Article
Information
RAIRO - Operations Research , Volume 34 , Issue 2 , April 2000 , pp. 183 - 197
Copyright
© EDP Sciences, 2000

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