Fuzzy Multi-objective Permutation Flow Shop Scheduling Problem with Fuzzy Processing Times under Learning and Aging Effects | ||
| Journal of Quality Engineering and Production Optimization | ||
| مقاله 6، دوره 3، شماره 2، بهمن 2018، صفحه 77-98 اصل مقاله (976.22 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22070/jqepo.2018.1841.1039 | ||
| نویسندگان | ||
| Farid Najari؛ Mohammad Alaghebandha؛ Mohammad Mohammadi* ؛ Mohammad Ali Sobhanallahi | ||
| Kharazmi University | ||
| چکیده | ||
| In industries machine maintenance is used in order to avoid untimely machine fails as well as to improve production effectiveness. This research regards a permutation flow shop scheduling problem with aging and learning effects considering maintenance process. In this study, it is assumed that each machine may be subject to at most one maintenance activity during the planning horizon. The objectives aim to minimize the makespan, tardiness of jobs, tardiness cost while maximizing net present value, simultaneously. Due to complexity and Np-hardness of the problem, two Pareto-based multi-objective evolutionary algorithms including non-dominated ranked genetic algorithm (NRGA) and non-dominated sorting genetic algorithm (NSGA-II) are proposed to attain Pareto solutions. In order to demonstrate applicability of the proposed methodology, a real-world application in polymer manufacturing industry is considered. | ||
| کلیدواژهها | ||
| Permutation flow shop؛ Aging and Learning Effect؛ Maintenance؛ Case study | ||
| مراجع | ||
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