A Self-Adaptive Differential Evolution Algorithm for Scheduling a Single Batch-Processing Machine With Arbitrary Job Sizes and Release Times
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 const...
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| Published in: | IEEE transactions on cybernetics Vol. 51; no. 3; pp. 1430 - 1442 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United States
IEEE
01.03.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 2168-2267, 2168-2275, 2168-2275 |
| Online Access: | Get full text |
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| Abstract | 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. |
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| AbstractList | 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. 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.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. |
| Author | Zhang, Qingfu Zheng, Xu Xing, Lining Zhou, Shengchao Du, Ni Wang, Ling |
| Author_xml | – sequence: 1 givenname: Shengchao orcidid: 0000-0001-7761-6346 surname: Zhou fullname: Zhou, Shengchao email: zhousc@mail.ustc.edu.cn organization: School of Automation, Central South University, Changsha, China – sequence: 2 givenname: Lining orcidid: 0000-0002-6983-4244 surname: Xing fullname: Xing, Lining email: xinglining@gmail.com organization: School of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, China – sequence: 3 givenname: Xu orcidid: 0000-0002-3773-7845 surname: Zheng fullname: Zheng, Xu email: scott@mail.ustc.edu.cn organization: School of Management, University of Science and Technology of China, Hefei, China – sequence: 4 givenname: Ni surname: Du fullname: Du, Ni email: ni.du@hunau.edu.cn organization: School of Economics, Hunan Agricultural University, Changsha, China – sequence: 5 givenname: Ling orcidid: 0000-0001-8964-6454 surname: Wang fullname: Wang, Ling email: wangling@tsinghua.edu.cn organization: Department of Automation, Tsinghua University, Beijing, China – sequence: 6 givenname: Qingfu surname: Zhang fullname: Zhang, Qingfu email: qingfu.zhang@cityu.edu.hk organization: Department of Computer Science, City University of Hong Kong, Hong Kong |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31567106$$D View this record in MEDLINE/PubMed |
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| Snippet | 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... |
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| SubjectTerms | Adaptive algorithms Algorithms Batch-processing machine (BPM) differential evolution (DE) Dynamic programming Evolutionary algorithms Evolutionary computation Genetic algorithms Heuristic algorithms Job shop scheduling Mutation operator adaptation Optimal scheduling parameter adaptation Scheduling |
| Title | A Self-Adaptive Differential Evolution Algorithm for Scheduling a Single Batch-Processing Machine With Arbitrary Job Sizes and Release Times |
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