Optimisation of fault-tolerant fabric-cutting schedules using genetic algorithms and fuzzy set theory

被引:38
|
作者
Mok, P. Y.
Kwong, C. K. [1 ]
Wong, W. K.
机构
[1] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Kowloon, Hong Kong, Peoples R China
[2] Hong Kong Polytech Univ, Inst Text & Clothing, Kowloon, Hong Kong, Peoples R China
关键词
genetic algorithms; fuzzy set theory; parallel machine scheduling; fabric cutting;
D O I
10.1016/j.ejor.2005.12.021
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
in apparel industry, manufacturers developed standard allowed minutes (SAMs) databases on various manufacturing operations in order to facilitate better scheduling, while effective production schedules ensure smoothness of downstream operations. As apparel manufacturing environment is fuzzy and dynamic, rigid production schedules based on SAMs become futile in the presence of any uncertainty. In this paper, a fuzzification scheme is proposed to fuzzify the static standard time so as to incorporate some uncertainties, in terms of both job-specific and human related factors, into the fabric-cutting scheduling problem. A genetic optimisation procedure is also proposed to search for fault-tolerant schedules using genetic algorithms, such that makespan and scheduling uncertainties are minimised. Two sets of real production data were collected to validate the proposed method. Experimental results indicate that the genetically optimised fault-tolerant schedules not only improve the operation performance but also minimise the scheduling risks. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:1876 / 1893
页数:18
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