Intelligent optimization algorithm library for assembly sequence planning of products

In order to tackle the hard problems of ″combinatorial explosion″ and ″blind search″, considering the disadvantages of single intelligent optimization algorithm for assembly sequence planning, an approach to resolve the problem of assembly sequence planning with intelligent optimization algorithm library (IAL) is proposed. The IAL is composed of an algorithm advisor and an algorithm pool. The most suitable algorithm will be provided to assembly planners by the algorithm advisor according to the description of the assembly planning problems, the quantified reference indices of algorithm performance and the empirical formulas. The improved genetic algorithm (GA), ant colony algorithm (AC) and simulated annealing algorithm (SA) have been implemented and stored in the algorithm pool. The evaluation index system of optimization algorithms and the optimization model of assembly sequence planning are also established. The operational procedure of the IAL is described. Finally, an illustrative example (cork-driver) is given to verify the rationality of the algorithms suggested by the IAL.