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

被引:24
|
作者
Kemmoe, Sylverin [1 ]
Lamy, Damien [2 ]
Tchernev, Nikolay [2 ]
机构
[1] Clermont Auvergne Univ, CRCGM, EA 3849, Clermont Ferrand, France
[2] Clermont Auvergne Univ, LIMOS, UMR 6158, Aubiere, France
关键词
job-shop; scheduling; energy efficient manufacturing; metaheuristics; integer programming; ADAPTIVE SEARCH PROCEDURE; TOTAL WEIGHTED TARDINESS; GENETIC ALGORITHM; SCHEDULING PROBLEMS; ENERGY-CONSUMPTION; LOCAL SEARCH; EFFICIENCY; SELECTION; SEQUENCE;
D O I
10.1080/00207543.2017.1321801
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:6011 / 6032
页数:22
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