An α-fuzzy goal approximate algorithm for solving fuzzy multiple objective linear programming problems

Jie Lu, Da Ruan, Fengjie Wu, Guangquan Zhang, Erik Laes, Benny Carlé

Research outputpeer-review


Multiple conflicting objectives in many decision making problems can be well described by multiple objective linear programming (MOLP) models. This paper deals with the vague and imprecise information in a multiple objective problem by fuzzy numbers to represent parameters of an MOLP model. This so-called fuzzy MOLP (or FMOLP) model will reflect some uncertainty in the problem solution process since most decision makers often have imprecise goals for their decision objectives. This study proposes an approximate algorithm based on a fuzzy goal optimization under the satisfactory degree α to handle both fuzzy and imprecise issues. The concept of a general fuzzy number is used in the proposed algorithm for an FMOLP problem with fuzzy parameters. As a result, this algorithm will allow decision makers to provide fuzzy goals in any form of membership functions.
Original languageEnglish
Pages (from-to)259-267
JournalSoft Computing
Issue number3
StatePublished - Feb 2007

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