An Efficient Heuristic for a Real-Life OAS Problem
Inspired by a real-life manufacturing problem, we present a mathematical model and a heuristic that solves it. A desired solution needs not only to maximize the company's profit but must also be easy to interpret by the members of the management. The considered problem is thus a variant of the...
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| Format: | Article |
| Language: | English |
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Wrocław University of Science and Technology
2025-01-01
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| Series: | Operations Research and Decisions |
| Online Access: | https://ord.pwr.edu.pl/assets/papers_archive/ord2025vol35no1_1.pdf |
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| _version_ | 1850100375730782208 |
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| author | Marcin Anholcer Andrzej Żak |
| author_facet | Marcin Anholcer Andrzej Żak |
| author_sort | Marcin Anholcer |
| collection | DOAJ |
| description | Inspired by a real-life manufacturing problem, we present a mathematical model and a heuristic that solves it. A desired solution needs not only to maximize the company's profit but must also be easy to interpret by the members of the management. The considered problem is thus a variant of the order acceptance and scheduling (OAS) problem, which can be solved using known heuristics. Our approach is different because we study the mechanism by which setup times arise, unlike other approaches where setup times are treated as parts of the instance. This enables us to develop a very fast and efficient heuristic, formulate a MILP model that can be applied to solve much larger problems than previously known methods, and ultimately meet decision-makers' expectations. We prove the efficiency of the presented method by comparing its results with the optimum obtained by a state-of-the-art solver. We also briefly discuss a case study that arose in a food industry company in Poland. (original abstract) |
| format | Article |
| id | doaj-art-be74de0f130645fab7eee1648955f18b |
| institution | DOAJ |
| issn | 2081-8858 2391-6060 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wrocław University of Science and Technology |
| record_format | Article |
| series | Operations Research and Decisions |
| spelling | doaj-art-be74de0f130645fab7eee1648955f18b2025-08-20T02:40:18ZengWrocław University of Science and TechnologyOperations Research and Decisions2081-88582391-60602025-01-01vol. 35no. 1120171707815An Efficient Heuristic for a Real-Life OAS ProblemMarcin Anholcer0Andrzej Żak1Poznań University of Economics and Business, Poznań, PolandAGH University, Kraków, PolandInspired by a real-life manufacturing problem, we present a mathematical model and a heuristic that solves it. A desired solution needs not only to maximize the company's profit but must also be easy to interpret by the members of the management. The considered problem is thus a variant of the order acceptance and scheduling (OAS) problem, which can be solved using known heuristics. Our approach is different because we study the mechanism by which setup times arise, unlike other approaches where setup times are treated as parts of the instance. This enables us to develop a very fast and efficient heuristic, formulate a MILP model that can be applied to solve much larger problems than previously known methods, and ultimately meet decision-makers' expectations. We prove the efficiency of the presented method by comparing its results with the optimum obtained by a state-of-the-art solver. We also briefly discuss a case study that arose in a food industry company in Poland. (original abstract)https://ord.pwr.edu.pl/assets/papers_archive/ord2025vol35no1_1.pdf |
| spellingShingle | Marcin Anholcer Andrzej Żak An Efficient Heuristic for a Real-Life OAS Problem Operations Research and Decisions |
| title | An Efficient Heuristic for a Real-Life OAS Problem |
| title_full | An Efficient Heuristic for a Real-Life OAS Problem |
| title_fullStr | An Efficient Heuristic for a Real-Life OAS Problem |
| title_full_unstemmed | An Efficient Heuristic for a Real-Life OAS Problem |
| title_short | An Efficient Heuristic for a Real-Life OAS Problem |
| title_sort | efficient heuristic for a real life oas problem |
| url | https://ord.pwr.edu.pl/assets/papers_archive/ord2025vol35no1_1.pdf |
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