A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem
Abstract Hybrid flow shop (HFS) environments are prevalent in various industries, including glass, steel, paper, and textiles, posing complex scheduling challenges. This paper introduces a novel approach employing Variable Neighborhood Search (VNS) to address the HFS scheduling problem, with a prima...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-02-01
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| Series: | Journal of Big Data |
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| Online Access: | https://doi.org/10.1186/s40537-025-01085-x |
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| author | Filip Vidojević Andrijana Džamić Dušan Džamić Miroslav Marić |
| author_facet | Filip Vidojević Andrijana Džamić Dušan Džamić Miroslav Marić |
| author_sort | Filip Vidojević |
| collection | DOAJ |
| description | Abstract Hybrid flow shop (HFS) environments are prevalent in various industries, including glass, steel, paper, and textiles, posing complex scheduling challenges. This paper introduces a novel approach employing Variable Neighborhood Search (VNS) to address the HFS scheduling problem, with a primary focus on minimizing makespan. The fundamental innovation lies in the fusion of VNS with domain-specific strategies, harnessing the adaptability of VNS. Departing significantly from conventional HFS approaches, our methodology incorporates a special encoding that allows jobs to wait strategically, even when free machines are available. This approach trades immediate machine utilization for the potential of improved makespan. Additionally, using this encoding, a proper decomposition of the problem is feasible. This innovative strategy aims to balance machine load while optimizing the overall scheduling performance. Experimental testing demonstrates the effectiveness of the proposed approach in comparison to existing methods. |
| format | Article |
| id | doaj-art-ea4a9e4e82074c4d9c2b8442b362efd2 |
| institution | Kabale University |
| issn | 2196-1115 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj-art-ea4a9e4e82074c4d9c2b8442b362efd22025-02-02T12:28:30ZengSpringerOpenJournal of Big Data2196-11152025-02-0112112410.1186/s40537-025-01085-xA novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problemFilip Vidojević0Andrijana Džamić1Dušan Džamić2Miroslav Marić3Faculty of Mathematics, University of BelgradeFaculty of Organizational Sciences, University of BelgradeFaculty of Organizational Sciences, University of BelgradeFaculty of Mathematics, University of BelgradeAbstract Hybrid flow shop (HFS) environments are prevalent in various industries, including glass, steel, paper, and textiles, posing complex scheduling challenges. This paper introduces a novel approach employing Variable Neighborhood Search (VNS) to address the HFS scheduling problem, with a primary focus on minimizing makespan. The fundamental innovation lies in the fusion of VNS with domain-specific strategies, harnessing the adaptability of VNS. Departing significantly from conventional HFS approaches, our methodology incorporates a special encoding that allows jobs to wait strategically, even when free machines are available. This approach trades immediate machine utilization for the potential of improved makespan. Additionally, using this encoding, a proper decomposition of the problem is feasible. This innovative strategy aims to balance machine load while optimizing the overall scheduling performance. Experimental testing demonstrates the effectiveness of the proposed approach in comparison to existing methods.https://doi.org/10.1186/s40537-025-01085-xHybrid flow shopVariable neighborhood searchSchedulingMathematical modelling |
| spellingShingle | Filip Vidojević Andrijana Džamić Dušan Džamić Miroslav Marić A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem Journal of Big Data Hybrid flow shop Variable neighborhood search Scheduling Mathematical modelling |
| title | A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem |
| title_full | A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem |
| title_fullStr | A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem |
| title_full_unstemmed | A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem |
| title_short | A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem |
| title_sort | novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem |
| topic | Hybrid flow shop Variable neighborhood search Scheduling Mathematical modelling |
| url | https://doi.org/10.1186/s40537-025-01085-x |
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