期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 55, 期 20, 页码 6011-6032出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2017.1321801
关键词
job-shop; scheduling; energy efficient manufacturing; metaheuristics; integer programming
资金
- French Public Investment Bank (BPI)
- ECOTHER project
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 (GRASPxELS) metaheuristic is designed. The GRASPxELS is compared with two other metaheuristics: a Variable Neighbourhood Search and a Memetic Algorithm. The GRASPxELS is also compared with several algorithms developed in the literature for the classical job-shop problem. Results show the relevancy of the metaheuristic approaches both in terms of computational time and quality of solutions.
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