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Recent advances in multiobjective evolutionary algorithm for manufacturing scheduling

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Indexed by:会议论文

Date of Publication:2013-10-16

Included Journals:EI、Scopus

Volume:2

Page Number:1480-1494

Abstract:Manufacturing scheduling is one of the important and complex combinatorial optimization problems in manufacturing system, where it can have a major impact on the productivity of a production process. Moreover, most of scheduling problems fall into the class of NP-hard combinatorial problems. In this paper, we concern with the design of multiobjective evolutionary algorithms (MOEAs) to solve a variety of manufacturing scheduling problems. In particularly, the fitness assignment mechanism and evolutionary representations as well as the hybrid evolutionary operations are introduced. Also, several applications of EAs to the different types of manufacturing scheduling problems are illustrated. Through a variety of numerical experiments, the effectiveness of these Hybrid EAs (HEAs) in the widely applications of manufacturing scheduling problems are demonstrated. This paper also summarizes a classification of scheduling problems and the design way of EAs for the different types of manufacturing scheduling problems in which we apply EAs to job-shop scheduling problem (JSP; operation sequencing), flexible JSP model (FJSP; operation sequencing with resources assignment), assembly line balancing models (ALB; shipments grouping and assignment), integrated process planning and scheduling (IPPS; operation sequencing with multiple resources assignment). It is useful to guide how to investigate an effective EA for the practical manufacturing scheduling problems.

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