An evolutionary algorithm for assembly job shop with part sharing

Authors:
Felix T. S. Chan;T. C. Wong;L. Y. Chan
Affiliations:
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Pokfulam Road, Hong Kong
Venue:
Computers and Industrial Engineering
Year:
2009

Citing 10
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Abstract

Assembly job shop problem (AJSP) is an extension of classical job shop problem (JSP). AJSP first starts with a JSP and appends an assembly stage after job completion. Lot Streaming (LS) technique is defined as the process of splitting lots into sub-lots such that successive operation can be overlapped. In this paper, the previous study of LS to AJSP is extended by allowing part sharing among distinct products. In addition to the use of simple dispatching rules (SDRs), an evolutionary approach with genetic algorithm (GA) is proposed to solve the research problem. A number of test problems were conducted to examine the performance of the proposed algorithm. Computational results suggested that the proposed algorithm can outperform the previous one, and can work well with respect to the objective function. Also, the inherent conflicting relationship between the primary objective and the system measurements can be addressed.