Solution methods for scheduling problems with sequence-dependent deterioration and maintenance events
| Autor: | Maxence Delorme, Manuel Iori, Nilson Felipe Matos Mendes |
|---|---|
| Přispěvatelé: | Econometrics and Operations Research, Research Group: Operations Research |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Information Systems and Management General Computer Science Computer science Iterated local search Maintenance 0211 other engineering and technologies Metaheuristic 02 engineering and technology Management Science and Operations Research Industrial and Manufacturing Engineering Scheduling (computing) Set (abstract data type) Factor (programming language) 0502 economics and business Deterioration Integer programming computer.programming_language Mathematical models Scheduling 050210 logistics & transportation 021103 operations research Job shop scheduling Mathematical model 05 social sciences Modeling and Simulation computer |
| Zdroj: | European Journal of Operational Research, 295(3), 823-837. Elsevier Science BV |
| ISSN: | 1872-6860 0377-2217 |
| Popis: | In this work, we study the problem of scheduling jobs and maintenance activities on a set of unrelated parallel machines, by considering that the processing time of a job increases according to a deterioration factor that depends both on the machine and on the set of jobs the machine has processed since its last maintenance. The objective we consider is to minimize the makespan. We introduce four mixed integer linear programming models, two of which using big-M constraints and the other two using an exponential number of variables. We also propose an iterated local search metaheuristic to tackle large size instances and we provide empirical evidence of the performance of the proposed approaches by means of extensive computational experiments. |
| Databáze: | OpenAIRE |
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