A novel fuzzy model for multi-objective permutation flow shop scheduling problem with fuzzy processing time

Fuyu Yuan,Minghao Yin,Xin Xu

doi:10.1177/1687814019843699

Abstract

This article proposes a novel fuzzy model for solving fuzzy multi-objective permutation flow shop scheduling problem with fuzzy processing time. Specifically, two fuzzy objectives, that is, the fuz...

Highlights

In recent years, scheduling problems have played an important role in both manufacturing system and traffic arrangement
As for the objectives of permutation flow shop scheduling problem (PFSSP), a variety of criterions have been presented according to different considerations, such as performance-oriented optimizations1, energy-related optimizations5, and environment-aware optimizations6
Note that the classical MOPFSSP cannot model some practical conditions owing to the fact that they are incapable of depicting the uncertain processing time

Summary

Introduction

In recent years, scheduling problems have played an important role in both manufacturing system and traffic arrangement. Nakhaeinejad and Nahavandi proposed an interactive method for solving the multi-objective fuzzy flow shop scheduling problem with the aim to minimize makespan, mean flow time, and machine idle time simultaneously. Behnamian and Fatemi Ghomi performed a bi-level algorithm, including random key genetic algorithm and particle swarm optimization algorithm, for the bi-objective hybrid flow shop scheduling problems with fuzzy processing time, sequence-dependent setup times, and due dates Different from those papers mentioned above, in this article, a novel fuzzy model of the FMOPFSSP with two fuzzy objectives, that is, the fuzzy makespan and the fuzzy total flow time, is proposed. For solving the FMOPFSSP, an efficient algorithm called fuzzy multi-objective local search-based decomposition (FMOLSD) is proposed. N: the population size nls: the max number of further local search pL : the current population pE :the external population pp :used in FuzzyParetoLoaclSearch

While the stopping criterion is not met do

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Conclusion and future work