An Enhanced Assembly Planning Approach Using a Multi-Objective Genetic Algorithm

Abstract This paper proposes an assembly planning approach using a multi-objective genetic algorithm (GA). The influence of tolerance and clearance on product assemblability in different assembly sequences is considered and used as a constraint in assembly planning. For a more comprehensive search for feasible non-dominated solutions, this paper proposes a multi-objective genetic algorithm that establishes different fitness functions through a fuzzy weight distribution algorithm. It also considers the experience of the decision maker. The results of the case study are given to verify the proposed approach.

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