Two-objective fuzzy job shop scheduling through genetic algorithm

Abstract

This paper discusses fuzzy job shop scheduling considering the fuzzy processing time and the fuzzy duetime, and formulates the fuzzy job shop scheduling problem considering two objects, namely, minimization of the maximum fuzzy completion time and maximization of the average agreement index. For each of the functions in the formulated two-objective fuzzy job shop scheduling problem, the fuzzy goal of the decision-maker is specified by a linear membership function, and then an approximate solution method is proposed, where the genetic algorithm is used for the problem, which integrates the membership functions by the fuzzy decision formulated by Bellman and Zadeh. As numerical examples, 6 × 6 and 10 × 10 two-objective fuzzy job shop scheduling problems are considered. Comparing the results to those by simulated annealing, the effectiveness of the proposed method is demonstrated. © 2000 Scripta Technica, Electron Comm Jpn Pt 3, 84(4): 60–68, 2001