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Evolutional Algorithm in Solving Flexible Job Shop Scheduling Problem with Uncertainties

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Indexed by:会议论文

Date of Publication:2015-01-01

Included Journals:CPCI-S

Page Number:1009-1015

Key Words:Condition based maintenance; Flexible job shop scheduling problem; Genetic algorithm; Ant colony optimization; Artificial bee algorithm

Abstract:In recent years, the necessity of considering uncertainty in scheduling problem is recognized by many scholars and practitioners, but there are still not effective methods to deal with uncertainty. This paper focuses on the flexible job shop scheduling problem (FJSP). Uncertainties in FJSP includes many aspects, such as the urgently arrival jobs, the uncertain working condition of the machines, etc. In this paper, we propose an inserting algorithm (IA), which can be used to treat the necessary machine maintenance for reducing unavailability of machines. We use the condition based maintenance (CBM) to reduce unavailability of machines. A problem focused in this paper is the flexible job shop scheduling problem with preventive maintenance (FJSPPM). An inserting algorithm (IA) is utilized to add PM into a preschedule scheme of FJSP which is obtained through an evolutional algorithm. Furthermore, a new better solution for an instance in benchmark of FJSP is obtained.

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