A Hybrid Method for the Parallel-Flow Shop-Scheduling Problem
In this study, we have dealt with a scheduling problem that has not been studied enough: the parallel-flow shop-scheduling problem. Its difficulty lies in the fact that it consists of two sub-problems: the assignment of jobs to workshops and the scheduling of these jobs once assigned. Due to the com...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Computer Sciences & Mathematics Forum |
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| Online Access: | https://www.mdpi.com/2813-0324/7/1/14413 |
| _version_ | 1797381442157674496 |
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| author | Milad Mansouri Younes Bahmani Hacene Smadi |
| author_facet | Milad Mansouri Younes Bahmani Hacene Smadi |
| author_sort | Milad Mansouri |
| collection | DOAJ |
| description | In this study, we have dealt with a scheduling problem that has not been studied enough: the parallel-flow shop-scheduling problem. Its difficulty lies in the fact that it consists of two sub-problems: the assignment of jobs to workshops and the scheduling of these jobs once assigned. Due to the complexity of the research problem, we propose a hybridization of two well-known optimization algorithms, a bio-inspired meta-heuristic algorithm (Particle Swarm Optimization—PSO) and a local search algorithm (tabu search, TS), with the aim of minimizing the maximum execution time of all jobs within constraints. The purpose of this hybridization is to combine the strengths of the two methods in order to obtain more efficient results than those achieved by classic methods. The concept of the proposed method is to start by generating a set of near-optimal solutions by the PSO meta-heuristic algorithm. Then, the TS algorithm refines and improves these solutions in order to attain the optimal solution. |
| first_indexed | 2024-03-08T20:52:33Z |
| format | Article |
| id | doaj.art-3b25911ebff64fe596bd8608d4ae85a3 |
| institution | Directory Open Access Journal |
| issn | 2813-0324 |
| language | English |
| last_indexed | 2024-03-08T20:52:33Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computer Sciences & Mathematics Forum |
| spelling | doaj.art-3b25911ebff64fe596bd8608d4ae85a32023-12-22T14:02:03ZengMDPI AGComputer Sciences & Mathematics Forum2813-03242023-04-01711441310.3390/IOCMA2023-14413A Hybrid Method for the Parallel-Flow Shop-Scheduling ProblemMilad Mansouri0Younes Bahmani1Hacene Smadi2Laboratory of Automation and Manufacturing Engineering, University of Batna 2, Batna 05000, AlgeriaLaboratory of Automation and Manufacturing Engineering, University of Batna 2, Batna 05000, AlgeriaLaboratory of Automation and Manufacturing Engineering, University of Batna 2, Batna 05000, AlgeriaIn this study, we have dealt with a scheduling problem that has not been studied enough: the parallel-flow shop-scheduling problem. Its difficulty lies in the fact that it consists of two sub-problems: the assignment of jobs to workshops and the scheduling of these jobs once assigned. Due to the complexity of the research problem, we propose a hybridization of two well-known optimization algorithms, a bio-inspired meta-heuristic algorithm (Particle Swarm Optimization—PSO) and a local search algorithm (tabu search, TS), with the aim of minimizing the maximum execution time of all jobs within constraints. The purpose of this hybridization is to combine the strengths of the two methods in order to obtain more efficient results than those achieved by classic methods. The concept of the proposed method is to start by generating a set of near-optimal solutions by the PSO meta-heuristic algorithm. Then, the TS algorithm refines and improves these solutions in order to attain the optimal solution.https://www.mdpi.com/2813-0324/7/1/14413parallel-flow shopschedulingtabu searchparticle swarm optimizationmakespan |
| spellingShingle | Milad Mansouri Younes Bahmani Hacene Smadi A Hybrid Method for the Parallel-Flow Shop-Scheduling Problem Computer Sciences & Mathematics Forum parallel-flow shop scheduling tabu search particle swarm optimization makespan |
| title | A Hybrid Method for the Parallel-Flow Shop-Scheduling Problem |
| title_full | A Hybrid Method for the Parallel-Flow Shop-Scheduling Problem |
| title_fullStr | A Hybrid Method for the Parallel-Flow Shop-Scheduling Problem |
| title_full_unstemmed | A Hybrid Method for the Parallel-Flow Shop-Scheduling Problem |
| title_short | A Hybrid Method for the Parallel-Flow Shop-Scheduling Problem |
| title_sort | hybrid method for the parallel flow shop scheduling problem |
| topic | parallel-flow shop scheduling tabu search particle swarm optimization makespan |
| url | https://www.mdpi.com/2813-0324/7/1/14413 |
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