4.7 Article Proceedings Paper

A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty

期刊

JOURNAL OF INTELLIGENT MANUFACTURING
卷 21, 期 1, 页码 65-73

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SPRINGER
DOI: 10.1007/s10845-008-0161-x

关键词

Job shop Scheduling; Uncertain duration; Multiobjective optimisation

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In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly active schedules. Experimental results are presented for several problem instances, solved by the GA according to the proposed model, considering three objectives: makespan, tardiness and idleness. The results illustrate the potential of the proposed multiobjective model and genetic algorithm.

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