Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/42934
Title: Optimisation of fault-tolerant fabric-cutting schedules using genetic algorithms and Fuzzy Set Theory
Authors: Kwong, CK
Wong, WK
Mok, PY
Keywords: Genetic algorithms
Fuzzy set theory
Parallel machine scheduling
Fabric cutting
Issue Date: 2007
Publisher: North-Holland
Source: European journal of operational research, 2007, v. 177, no. 3, p. 1876-1893 How to cite?
Journal: European journal of operational research 
Abstract: 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.
URI: http://hdl.handle.net/10397/42934
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2005.12.021
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