Ant colony optimization algorithm for total weighted completion time minimization on non-identical batch machines

被引:19
|
作者
Zhang, Han [1 ,2 ]
Jia, Zhao-hong [1 ,2 ]
Li, Kai [3 ]
机构
[1] Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei, Peoples R China
[2] Anhui Univ, Sch Comp Sci & Technol, Hefei 230039, Anhui, Peoples R China
[3] Hefei Univ Technol, Sch Management, Hefei 230009, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
Scheduling; Parallel batch machines; Arbitrary capacities; Ant colony optimization (ACO); The total weighted completion time; INCOMPATIBLE JOB FAMILIES; HYBRID GENETIC ALGORITHM; PROCESSING MACHINE; MINIMIZING MAKESPAN; PARALLEL MACHINES; RELEASE TIMES; SIZES; CAPACITIES; ARRIVALS; BRANCH;
D O I
10.1016/j.cor.2020.104889
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper aims at the problem of scheduling a set of jobs with arbitrary sizes on parallel batch processing machines with arbitrary capacities. The optimization objective is to minimize the total weighted completion time of jobs. After describing the studied problem, we analyze its complexity and present a lower bound of the problem. A heuristic is provided to solve the problem firstly. Then, with the proposed first job selection strategy based on the weights of jobs, two algorithms based on the ant system and the max-min ant system, respectively, are designed to address the problem. Through extensive experiments, the performance of the proposed algorithms is compared with several state-of-the-art algorithms. The comparative results verify effectiveness and efficiency of the proposed algorithms. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:19
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