Multi-objective optimization for dynamic single-machine scheduling

Authors:
Li Nie;Liang Gao;Peigen Li;Xiaojuan Wang
Affiliations:
The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China
Venue:
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
Year:
2011

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Abstract

In this paper, a multi-objective evolutionary algorithm based on gene expression programming (MOGEP) is proposed to construct scheduling rules (SRs) for dynamic single-machine scheduling problem (DSMSP) with job release dates. In MOGEP a fitness assignment scheme, diversity maintaining strategy and elitist strategy are incorporated on the basis of original GEP. Results of simulation experiments show that the MOGEP can construct effective SRs which contribute to optimizing multiple scheduling measures simultaneously.