Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job Shop
Green scheduling is not only an effective way to achieve green manufacturing but also an effective way for modern manufacturing enterprises to achieve energy conservation and emission reduction. The double-flexible job shop scheduling problem (DFJSP) considers both machine flexibility and worker fle...
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| Format: | Article |
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MDPI AG
2021-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/1/205 |
| _version_ | 1797499644340600832 |
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| author | Changping Liu Yuanyuan Yao Hongbo Zhu |
| author_facet | Changping Liu Yuanyuan Yao Hongbo Zhu |
| author_sort | Changping Liu |
| collection | DOAJ |
| description | Green scheduling is not only an effective way to achieve green manufacturing but also an effective way for modern manufacturing enterprises to achieve energy conservation and emission reduction. The double-flexible job shop scheduling problem (DFJSP) considers both machine flexibility and worker flexibility, so it is more suitable for practical production. First, a multi-objective mixed-integer programming model for the DFJSP with the objectives of optimizing the makespan, total worker costs, and total influence of the green production indicators is formulated. Considering the characteristics of the problem, three-layer salp individual encoding and decoding methods are designed for the multi-objective hybrid salp swarm algorithm (MHSSA), which is hybridized with the Lévy flight, the random probability crossover operator, and the mutation operator. In addition, the influence of the parameter setting on the MHSSA in solving the DFJSP is investigated by means of the Taguchi method of design of experiments. The simulation results for benchmark instances show that the MHSSA can effectively solve the proposed problem and is significantly better than the MSSA and the MOPSO algorithm in the diversity, convergence, and dominance of the Pareto frontier. |
| first_indexed | 2024-03-10T03:50:22Z |
| format | Article |
| id | doaj.art-7eba8987c51349068eb9b4b569768dde |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T03:50:22Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7eba8987c51349068eb9b4b569768dde2023-11-23T11:09:21ZengMDPI AGApplied Sciences2076-34172021-12-0112120510.3390/app12010205Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job ShopChangping Liu0Yuanyuan Yao1Hongbo Zhu2Faculty of Management Engineering, Huaiyin Institute of Technology, Huaian 223200, ChinaCollege of Economics and Management, Suzhou Chienshiung Institute of Technology, Taicang 215411, ChinaFaculty of Mathematics and Physics, Huaiyin Institute of Technology, Huaian 223003, ChinaGreen scheduling is not only an effective way to achieve green manufacturing but also an effective way for modern manufacturing enterprises to achieve energy conservation and emission reduction. The double-flexible job shop scheduling problem (DFJSP) considers both machine flexibility and worker flexibility, so it is more suitable for practical production. First, a multi-objective mixed-integer programming model for the DFJSP with the objectives of optimizing the makespan, total worker costs, and total influence of the green production indicators is formulated. Considering the characteristics of the problem, three-layer salp individual encoding and decoding methods are designed for the multi-objective hybrid salp swarm algorithm (MHSSA), which is hybridized with the Lévy flight, the random probability crossover operator, and the mutation operator. In addition, the influence of the parameter setting on the MHSSA in solving the DFJSP is investigated by means of the Taguchi method of design of experiments. The simulation results for benchmark instances show that the MHSSA can effectively solve the proposed problem and is significantly better than the MSSA and the MOPSO algorithm in the diversity, convergence, and dominance of the Pareto frontier.https://www.mdpi.com/2076-3417/12/1/205double flexible job-shop schedulingmulti-objective optimizationhybrid salp swarm algorithmgreen shop scheduling |
| spellingShingle | Changping Liu Yuanyuan Yao Hongbo Zhu Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job Shop Applied Sciences double flexible job-shop scheduling multi-objective optimization hybrid salp swarm algorithm green shop scheduling |
| title | Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job Shop |
| title_full | Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job Shop |
| title_fullStr | Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job Shop |
| title_full_unstemmed | Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job Shop |
| title_short | Hybrid Salp Swarm Algorithm for Solving the Green Scheduling Problem in a Double-Flexible Job Shop |
| title_sort | hybrid salp swarm algorithm for solving the green scheduling problem in a double flexible job shop |
| topic | double flexible job-shop scheduling multi-objective optimization hybrid salp swarm algorithm green shop scheduling |
| url | https://www.mdpi.com/2076-3417/12/1/205 |
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