Optimizing the sum of maximum earliness and tardiness of the job shop scheduling problem

被引:52
|
作者
Yazdani, Maziar [1 ]
Aleti, Aldeida [2 ]
Khalili, Seyed Mohammad [1 ]
Jolai, Fariborz [1 ]
机构
[1] Univ Tehran, Univ Coll Engn, Dept Ind Engn, Tehran, Iran
[2] Monash Univ, Fac Informat Technol, Caulfield, Vic 3145, Australia
关键词
Job shop scheduling; Maximum earliness; Maximum tardiness; Imperialist competitive algorithm; Neighborhood search; IMPERIALIST COMPETITIVE ALGORITHM; PARTICLE SWARM OPTIMIZATION; HARMONY SEARCH ALGORITHM; MODEL GENETIC ALGORITHM; SINGLE-MACHINE; WEIGHTED TARDINESS; IMMUNE ALGORITHM; COLONY ALGORITHM; BOUND ALGORITHM; SETUP TIMES;
D O I
10.1016/j.cie.2017.02.019
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The sum of the maximum earliness and tardiness criteria is a new objective function for the job shop scheduling problem introduced in this work. A mixed integer linear programming (MIP) formulation of the job shop scheduling problem with the new objective function is developed. We design a set of experiments where we validate the MIP model on different problem sizes. This is one of the most difficult problems in combinatorial optimization, with even modest sized instances being computationally intractable. Getting inspiration from a number of advances in solving this notoriously difficult problem, we develop a new approximate optimization approach, which is based on the imperialist competitive algorithm hybridized with an efficient neighborhood search. The effectiveness of the proposed approach is demonstrated through an experimental evaluation. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:12 / 24
页数:13
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