Job-shop like manufacturing system with variable power threshold and operations with power requirements

Autor: Nikolay Tchernev, Damien Lamy, S. Kemmoe
Přispěvatelé: Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: International Journal of Production Research
International Journal of Production Research, Taylor & Francis, 2017, 55 (20), pp.6011-6032. ⟨10.1080/00207543.2017.1321801⟩
International Journal of Production Research, 2017, 55 (20), pp.6011-6032. ⟨10.1080/00207543.2017.1321801⟩
ISSN: 0020-7543
1366-588X
DOI: 10.1080/00207543.2017.1321801⟩
Popis: This paper addresses an important issue in manufacturing by considering the scheduling of a Job-shop like manufacturing system involving a power threshold that must not be exceeded over time. A power profile is attached to operations that must be scheduled. This power profile presents a consumption peak at the start of process in order to model most of real-world machining operations. These operations must be scheduled according to the instantly available power threshold. A mathematical formulation of the problem is proposed; its main goal is to minimise the total completion time of all operations. A set of instances is built based on classical format of instances for the Job-shop problem. As it is time-consuming to obtain exact solutions on these instances with the CPLEX solver, a Greedy Randomised Adaptive Search Procedure hybridised with an Evolutionary Local Search (GRASP × ELS) metaheuristic is designed. The GRASP × ELS is compared with two other metaheuristics: a Variable Neighbourhood Search and a ...
Databáze: OpenAIRE