Multiobjective Local Search for Mean-Variance Combinatorial Optimisation

• Type: Article in International Conference Proceedings Book
• Date: 2005

Authors

Claro, João (Author) FEUP; Pinho de Sousa, Jorge (Author) FEUP

Conference proceedings International

Title: MIC 2005 Conference Proceedings

Pages: 217-224

MIC 2005 - The 6th Metaheuristics International Conference

Vienna, Austria, August 22-26, 2005

Other information

Abstract (EN): In operational problems under uncertainty, the explicit consideration of risk concerns is a fundamental but often overlooked issue. Recently, however, there has been an increasing attention to this topic, in both literature and practice. With this background as motivation, we propose in this paper an approach based on multiobjective metaheuristics and sample approximations to tackle mean-variance models of stochastic combinatorial optimisation (SCO) problems. The potential of the approach, as a generic and efficient algorithm for the identification of good quality approximations to mean-risk efficient sets in SCO problems, is validated with an application to the static stochastic knapsack problem, involving a computational study whose results are discussed. The approach is able to handle several difficulties inherent to these problems, and the computational results, obtained with a straightforward implementation, are promising.

Language: Portuguese

Type (Professor's evaluation): Scientific