Volume 54, Number 5, September-October 2020
|Page(s)||1437 - 1452|
|Published online||23 July 2020|
A possibilistic optimization over an integer efficient set within a fuzzy environment
AMCD-RO-DGRSDT Laboratory, Faculty of Mathematics, Department of Operations Research USTHB, Bab-Ezzouar, Bp 32 El Alia, BEZ, 16121 Algiers, Algeria
* Corresponding author: email@example.com
Accepted: 14 August 2019
Optimizing a linear function over the efficient set of a Multiple Objective Integer Linear Programming (MOILP) problem is known as a difficult problem to deal with, since a discrete efficient set is generally not convex and not explicitly known. Such problem becomes more and more difficult when parameters are defined with uncertainty. In this work, we deal with problems of this type for which parameters are imprecise and are assumed to be trapezoidal fuzzy numbers. The method is based on possibility and necessity measures introduced in the literature by D. Dubois and H. Prade.
Mathematics Subject Classification: MSC 90C29 / MSC 03E72 / MSC 90C70
Key words: Multiple objective programming / discrete optimization / Fuzzy parameters / possibility measure / necessity measure
© EDP Sciences, ROADEF, SMAI 2020
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