Solving the energy-aware flexible job shop problem using a memetic algorithm
This article addresses the flexible job shop problem with interval processing times. Minimising makespan is a well-known scheduling objective that is widely used in many sectors; however, energy efficiency is gaining more importance as climate change intensifies. In this work, we minimise the makesp...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:ucreareposit::780c588e8fd7ea359935bdee00a022ce |
| Acceso en línea: | https://hdl.handle.net/10902/39912 |
| Access Level: | acceso abierto |
| Palabra clave: | Flexible job shop scheduling Interval Memetic algorithm Local search Lexicographic goal programming |
| Sumario: | This article addresses the flexible job shop problem with interval processing times. Minimising makespan is a well-known scheduling objective that is widely used in many sectors; however, energy efficiency is gaining more importance as climate change intensifies. In this work, we minimise the makespan and the total energy consumption using a lexicographic goal programming approach. A memetic algorithm that is composed of a genetic algorithm and a local search method is developed and tested to solve this problem. The results show that our approach manages to improve the best-known results. |
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