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.
机构:
Minist Educ, Key Lab Intelligent Comp & Signal Proc, Beijing, Peoples R China
Anhui Univ, Sch Comp Sci & Technol, Hefei 230039, Anhui, Peoples R ChinaMinist Educ, Key Lab Intelligent Comp & Signal Proc, Beijing, Peoples R China
Jia, Zhao-hong
Wang, Chao
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Anhui Univ, Sch Comp Sci & Technol, Hefei 230039, Anhui, Peoples R ChinaMinist Educ, Key Lab Intelligent Comp & Signal Proc, Beijing, Peoples R China
Wang, Chao
Leung, Joseph Y. -T.
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Hefei Univ Technol, Sch Management, Hefei 230009, Anhui, Peoples R China
New Jersey Inst Technol, Dept Comp Sci, Newark, NJ 07102 USAMinist Educ, Key Lab Intelligent Comp & Signal Proc, Beijing, Peoples R China