An improved scatter search algorithm for solving job shop scheduling problems with parallel batch processing machine
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| Publicat a: | Scientific Reports (Nature Publisher Group) vol. 15, no. 1 (2025), p. 11872 |
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Nature Publishing Group
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| Accés en línia: | Citation/Abstract Full Text - PDF |
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| 001 | 3188186226 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2045-2322 | ||
| 024 | 7 | |a 10.1038/s41598-025-92761-8 |2 doi | |
| 035 | |a 3188186226 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 274855 |2 nlm | ||
| 245 | 1 | |a An improved scatter search algorithm for solving job shop scheduling problems with parallel batch processing machine | |
| 260 | |b Nature Publishing Group |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper addresses a hybrid processing system in automotive mold casting, which involves single processing machines and parallel batch processing machines. A job shop scheduling problem with parallel batch processing machines (JSP-PBPM) is developed, with the objective of minimizing the maximum completion time. First, a solution decoding strategy combined with the JSP-PBPM problem and a batch job addition algorithm is proposed. This approach addresses the impact of operation precedence relationships on conventional decoding strategies and aims to maximize the utilization of parallel batch processing machines for batch operations. Next, an Improved Scatter Search (ISS) algorithm is introduced to solve the problem. The ISS algorithm finds the optimal solution through several steps, including the construction of the initial population, improvement of the initial solution, creation of a reference set, generation of subsets, and refinement of the final solution. Finally, simulation experiments are conducted to verify the feasibility and effectiveness of the proposed algorithm and decoding strategy in solving such problems. | |
| 653 | |a Algorithms | ||
| 653 | |a Job shops | ||
| 653 | |a Batch processing | ||
| 653 | |a Economic | ||
| 773 | 0 | |t Scientific Reports (Nature Publisher Group) |g vol. 15, no. 1 (2025), p. 11872 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3188186226/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3188186226/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |