An efficient Pareto approach for solving the multi-objective flexible job-shop scheduling problem with regular criteria

被引:26
|
作者
Alberto Garcia-Leon, Andres [1 ,2 ]
Dauzere-Peres, Stephane [2 ,3 ]
Mati, Yazid [4 ]
机构
[1] Univ Ibague, Fac Ingn, Programa Ingn Ind, Ibague, Colombia
[2] Univ Clermont Auvergne, Mines St Etienne, Dept Mfg Sci & Logist, CNRS,UMR LIMOS 6158,CMP, Gardanne, France
[3] BI Norwegian Business Sch, Dept Accounting Auditing & Business Analyt, Oslo, Norway
[4] Qassim Univ, Coll Business & Econ, Buraydah, Saudi Arabia
关键词
Flexible job-shop scheduling; Multi-objective; Regular criteria; Pareto optimization; Local search; PARTICLE SWARM OPTIMIZATION; PATH-RELINKING; ALGORITHM; SEARCH; HYBRID;
D O I
10.1016/j.cor.2019.04.012
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, a general local search approach for the Multi-Objective Flexible Job-shop Scheduling Problem (MOFJSP) is proposed to determine a Pareto front for any combination of regular criteria. The approach is based on a disjunctive graph, a fast estimation function to evaluate moves and a hierarchical test to efficiently control the set of non-dominated solutions. Four search strategies using two neighborhood structures are developed. Numerical experiments are conducted on test instances of the literature with three sets of criteria to minimize and using metrics to evaluate and compare Pareto fronts. The results show that our approach provides sets of non-dominated solutions of good quality. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:187 / 200
页数:14
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