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Improving the Computational Efficiency in a Global Formulation (GLIDE) for Interactive Multiobjective Optimization
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
2012 (English)In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 197, no 1, 47-70 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we present a new general formulation for multiobjective optimization that can accommodate several interactive methods of different types (regarding various types of preference information required from the decision maker). This formulation provides a comfortable implementation framework for a general interactive system and allows the decision maker to conveniently apply several interactive methods in one solution process. In other words, the decision maker can at each iteration of the solution process choose how to give preference information to direct the interactive solution process, and the formulation enables changing the type of preferences, that is, the method used, whenever desired. The first general formulation, GLIDE, included eight interactive methods utilizing four types of preferences. Here we present an improved version where we pay special attention to the computational efficiency (especially significant for large and complex problems), by eliminating some constraints and parameters of the original formulation. To be more specific, we propose two new formulations, depending on whether the multiobjective optimization problem to be considered is differentiable or not. Some computational tests are reported showing improvements in all cases. The generality of the new improved formulations is supported by the fact that they can accommodate six interactive methods more, that is, a total of fourteen interactive methods, just by adjusting parameter values.

Place, publisher, year, edition, pages
Springer, 2012. Vol. 197, no 1, 47-70 p.
Keyword [en]
Multiobjective programming, Multiple objectives, Interactive methods, Reference point methods, Classification, Marginal rates of substitution, Global system, Pareto optimality
National Category
URN: urn:nbn:se:kth:diva-63800DOI: 10.1007/s10479-010-0831-xISI: 000307272400004OAI: diva2:482712

QC 20130214

Available from: 2012-04-23 Created: 2012-01-24 Last updated: 2013-02-14Bibliographically approved

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