Affiliations:
School of Science, Nanjing University of Science and Technology, Nanjing, Jiangsu, P.R. China
Correspondence:
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Corresponding author. Yuanguo Zhu, School of Science, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P.R. China. Tel.: +86 25 8431 5878; E-mail: [email protected].
Abstract: Flexible flow shop scheduling problems become more complex when uncertain factors are taken into consideration. Most literature are under the assumption that machines are continuous available. But, a machine can be unavailable for many reasons, such as breakdown and planned preventive maintenance. Once a machine breaks down, then the original schedule can not be executed and we must make the corresponding adjustment according to the actual situation. This paper deals with a flexible flow shop scheduling problem with uncertain processing and repair time subject to breakdowns. Machines are non-continuously available, i.e., they break down at arbitrary time instance not known in advance. The problem with breakdowns is modeled as a series of problems without breakdowns. To solve the problem, approaches including genetic algorithm and particle swarm optimization are used in this paper. A numerical example shows the effectiveness of the proposed approach.
