A Self-Adaptive Differential Evolution Algorithm for Scheduling a Single Batch-Processing Machine With Arbitrary Job Sizes and Release Times

被引:188
作者
Zhou, Shengchao [1 ]
Xing, Lining [2 ,3 ]
Zheng, Xu [4 ]
Du, Ni [5 ]
Wang, Ling [6 ]
Zhang, Qingfu [7 ,8 ]
机构
[1] Cent South Univ, Sch Automat, Changsha 410083, Peoples R China
[2] Cent South Univ Forestry & Technol, Sch Logist & Transportat, Changsha 410004, Peoples R China
[3] Natl Univ Def Technol, Sch Syst Engn, Changsha 410073, Peoples R China
[4] Univ Sci & Technol China, Sch Management, Hefei 230026, Peoples R China
[5] Hunan Agr Univ, Sch Econ, Changsha 410128, Peoples R China
[6] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[7] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
[8] City Univ Hong Kong, Shenzhen Res Inst, Shenzhen 518172, Peoples R China
基金
中国国家自然科学基金;
关键词
Optimal scheduling; Job shop scheduling; Heuristic algorithms; Genetic algorithms; Dynamic programming; Batch-processing machine (BPM); differential evolution (DE); operator adaptation; parameter adaptation; scheduling;
D O I
10.1109/TCYB.2019.2939219
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Batch-processing machines (BPMs) can process a number of jobs at a time, which can be found in many industrial systems. This article considers a single BPM scheduling problem with unequal release times and job sizes. The goal is to assign jobs into batches without breaking the machine capacity constraint and then sort the batches to minimize the makespan. A self-adaptive differential evolution algorithm is developed for addressing the problem. In our proposed algorithm, mutation operators are adaptively chosen based on their historical performances. Also, control parameter values are adaptively determined based on their historical performances. Our proposed algorithm is compared to CPLEX, existing metaheuristics for this problem and conventional differential evolution algorithms through comprehensive experiments. The experimental results demonstrate that our proposed self-adaptive algorithm is more effective than other algorithms for this scheduling problem.
引用
收藏
页码:1430 / 1442
页数:13
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