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Title A multiobjective metaheuristic for a mean-risk static stochastic knapsack problem
Edition
Call Number
ISBN/ISSN 0926-6003
Author(s) Claro,João
de Sousa, Jorge Pinho
Subject(s)
Classification
Series Title Computational Optimization and Applications
GMD Electronic Journal
Language English
Publisher Springer Netherlands
Publishing Year
Publishing Place Netherlands
Collation 24p
Abstract/Notes In this paper we address two major challenges presented by stochastic discrete
optimisation problems: the multiobjective nature of the problems, once risk
aversion is incorporated, and the frequent difficulties in computing exactly, or even
approximately, the objective function. The latter has often been handled with methods
involving sample average approximation, where a random sample is generated
so that population parameters may be estimated from sample statistics—usually the
expected value is estimated from the sample average.We propose the use of multiobjective
metaheuristics to deal with these difficulties, and apply a multiobjective local
search metaheuristic to both exact and sample approximation versions of a mean-risk
static stochastic knapsack problem. Variance and conditional value-at-risk are considered
as risk measures. Results of a computational study are presented, that indicate
the approach is capable of producing high-quality approximations to the efficient sets,
with a modest computational effort.
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