Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach
The management of industrial systems is done through different levels, ranging from strategic (designing the system), to tactical (planning the activities and assigning the resources) and operational (scheduling the activities). In this paper, we focus on the latter level by considering a real-world...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/3/1202 |
| _version_ | 1797406487945936896 |
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| author | Nathalie Klement Mohamed Amine Abdeljaouad Leonardo Porto Cristóvão Silva |
| author_facet | Nathalie Klement Mohamed Amine Abdeljaouad Leonardo Porto Cristóvão Silva |
| author_sort | Nathalie Klement |
| collection | DOAJ |
| description | The management of industrial systems is done through different levels, ranging from strategic (designing the system), to tactical (planning the activities and assigning the resources) and operational (scheduling the activities). In this paper, we focus on the latter level by considering a real-world scheduling problem from a plastic injection company, where the production process combines parallel machines and a set of resources. We present a scheduling algorithm that combines a metaheuristic and a list algorithm. Two metaheuristics are tested and compared when used in the proposed scheduling approach: the stochastic descent and the simulated annealing. The method’s performances are analyzed through an experimental study and the obtained results show that its outcomes outperform those of the scheduling policy conducted in a case-study company. Moreover, besides being able to solve large real-world problems in a reasonable amount of time, the proposed approach has a structure that makes it flexible and easily adaptable to several different planning and scheduling problems. Indeed, since it is composed by a reusable generic part, the metaheuristic, it is only required to develop a list algorithm adapted to the objective function and constraints of the new problem to be solved. |
| first_indexed | 2024-03-09T03:27:10Z |
| format | Article |
| id | doaj.art-3553871505f4437cbd42ce07db0b889a |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T03:27:10Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-3553871505f4437cbd42ce07db0b889a2023-12-03T15:00:49ZengMDPI AGApplied Sciences2076-34172021-01-01113120210.3390/app11031202Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization ApproachNathalie Klement0Mohamed Amine Abdeljaouad1Leonardo Porto2Cristóvão Silva3Arts et Métiers Institute of Technology, LISPEN, HESAM Université, 59000 Lille, FranceCEA Tech Hauts-de-France, 59000 Lille, FranceCEMMPRE, Department of Mechanical Engineering, University of Coimbra, 3030-790 Coimbra, PortugalCEMMPRE, Department of Mechanical Engineering, University of Coimbra, 3030-790 Coimbra, PortugalThe management of industrial systems is done through different levels, ranging from strategic (designing the system), to tactical (planning the activities and assigning the resources) and operational (scheduling the activities). In this paper, we focus on the latter level by considering a real-world scheduling problem from a plastic injection company, where the production process combines parallel machines and a set of resources. We present a scheduling algorithm that combines a metaheuristic and a list algorithm. Two metaheuristics are tested and compared when used in the proposed scheduling approach: the stochastic descent and the simulated annealing. The method’s performances are analyzed through an experimental study and the obtained results show that its outcomes outperform those of the scheduling policy conducted in a case-study company. Moreover, besides being able to solve large real-world problems in a reasonable amount of time, the proposed approach has a structure that makes it flexible and easily adaptable to several different planning and scheduling problems. Indeed, since it is composed by a reusable generic part, the metaheuristic, it is only required to develop a list algorithm adapted to the objective function and constraints of the new problem to be solved.https://www.mdpi.com/2076-3417/11/3/1202heuristicmetaheuristicsschedulinginjection molding |
| spellingShingle | Nathalie Klement Mohamed Amine Abdeljaouad Leonardo Porto Cristóvão Silva Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach Applied Sciences heuristic metaheuristics scheduling injection molding |
| title | Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach |
| title_full | Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach |
| title_fullStr | Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach |
| title_full_unstemmed | Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach |
| title_short | Lot-Sizing and Scheduling for the Plastic Injection Molding Industry—A Hybrid Optimization Approach |
| title_sort | lot sizing and scheduling for the plastic injection molding industry a hybrid optimization approach |
| topic | heuristic metaheuristics scheduling injection molding |
| url | https://www.mdpi.com/2076-3417/11/3/1202 |
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