Title: A hybrid genetic algorithm approach on multi-objective of assembly planning problem
Authors: Chen, RS
Lu, KY
Yu, SC
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
Keywords: assembly planning;genetic algorithm;assembly line balancing;multi-objective;design for assembly
Issue Date: 1-Sep-2002
Abstract: In practice, modeling an assembly system often requires assigning a set of operations to a set of workstations. The aim is to optimize some performance indices of an assembly line. This assignation is usually a tedious design procedure so a significant amount of manpower is required to obtain a good work plan. Poor assembly planning may significantly increase the cost of products and reduce productivity. However, these optimization problems fall into the class of NP-hard problems. Finding an optimal solution in an acceptable time is difficult, even using a powerful computer. This study presents a hybrid genetic algorithm approach to the problems of assembly planning with various objectives, including minimizing cycle time, maximizing workload smoothness, minimizing the frequency of tool change, minimizing the number of tools and machines used, and minimizing the complexity of assembly sequences. A self-tuning method was developed to correct infeasible-chromosomes. Several examples were employed to illustrate the proposed approach. Experimental results indicated that the proposed method can efficiently yield many alternative assembly plans to support the design and operation of a flexible assembly system. (C) 2003 Elsevier Science Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/S0952-1976(02)00073-8
http://hdl.handle.net/11536/28557
ISSN: 0952-1976
DOI: 10.1016/S0952-1976(02)00073-8
Journal: ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume: 15
Issue: 5
Begin Page: 447
End Page: 457
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