Intelligent optimization under blocking constraints: A novel iterated greedy algorithm for the hybrid flow shop group scheduling problem
This paper introduces a new flow shop combinatorial optimization problem, called the blocking hybrid flow shop group scheduling problem (BHFGSP). In the problem, no buffers exist between any adjacent machines, and a set of jobs with different sequence-dependent setup times needs to be scheduled and...
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| Published in: | Knowledge-based systems Vol. 258; p. 109962 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
22.12.2022
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| ISSN: | 0950-7051, 1872-7409 |
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| Abstract | This paper introduces a new flow shop combinatorial optimization problem, called the blocking hybrid flow shop group scheduling problem (BHFGSP). In the problem, no buffers exist between any adjacent machines, and a set of jobs with different sequence-dependent setup times needs to be scheduled and processed at organized manufacturing cells. We verify the correctness of the mathematical model of BHFGSP by using CPLEX. In this paper, we proposed a novel iterated greedy algorithm to solve the problem. The proposed algorithm has two key techniques. One is the decoding procedure that calculates the makespan of a job sequence, and the other is the neighborhood probabilistic selection strategies with families and blocking-based jobs. The performance of the proposed algorithm is investigated through a large number of numerical experiments. Comprehensive results show that the proposed algorithm is effective in solving BHFGSP. |
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| AbstractList | This paper introduces a new flow shop combinatorial optimization problem, called the blocking hybrid flow shop group scheduling problem (BHFGSP). In the problem, no buffers exist between any adjacent machines, and a set of jobs with different sequence-dependent setup times needs to be scheduled and processed at organized manufacturing cells. We verify the correctness of the mathematical model of BHFGSP by using CPLEX. In this paper, we proposed a novel iterated greedy algorithm to solve the problem. The proposed algorithm has two key techniques. One is the decoding procedure that calculates the makespan of a job sequence, and the other is the neighborhood probabilistic selection strategies with families and blocking-based jobs. The performance of the proposed algorithm is investigated through a large number of numerical experiments. Comprehensive results show that the proposed algorithm is effective in solving BHFGSP. |
| ArticleNumber | 109962 |
| Author | Han, Yuyan Pan, Quanke Qin, Haoxiang Wang, Yuting Li, Junqing Liu, Yiping |
| Author_xml | – sequence: 1 givenname: Haoxiang surname: Qin fullname: Qin, Haoxiang organization: School of Computer Science, Liaocheng University, Liaocheng, 252059, China – sequence: 2 givenname: Yuyan surname: Han fullname: Han, Yuyan email: hanyuyan@lcu-cs.com organization: School of Computer Science, Liaocheng University, Liaocheng, 252059, China – sequence: 3 givenname: Yuting surname: Wang fullname: Wang, Yuting email: wangyuting@lcu-cs.com organization: School of Computer Science, Liaocheng University, Liaocheng, 252059, China – sequence: 4 givenname: Yiping surname: Liu fullname: Liu, Yiping organization: The College of Computer Science and Electronic Engineering, Hunan University, 410082, China – sequence: 5 givenname: Junqing surname: Li fullname: Li, Junqing organization: School of Computer Science, Liaocheng University, Liaocheng, 252059, China – sequence: 6 givenname: Quanke surname: Pan fullname: Pan, Quanke organization: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China |
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| Keywords | Blocking Iterated greedy algorithm Makespan Hybrid flow shop group scheduling problem Neighborhood probabilistic selection strategies |
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