Abstract
This paper describes a hybrid approach to handle disassembly sequence planning for maintenance. The product under maintenance is first modeled using a novel hybrid graph known as Disassembly Constraint Graph (DCG) which embodies complete disassembly information and can be used to prune the search space of disassembly sequences. Subsequently, a novel Tabu-enhanced GA engine is invoked to generate the near optimal disassembly sequences. A case study was used to illustrate the effectiveness of the proposed approach. The details of the DCG, the TS-enhanced GA engine and the fitness function used are presented in this paper.
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