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Assembly sequence generation using genetic algorithm

An assembly sequence is considered to be optimal when it minimizes assembly cost while satisfying assembly constraints. to generate such sequences for robotic assembly, this paper proposes a method using a genetic algorithm (GA). This method denotes an assembly sequence as an individual, which is assigned a fitness related to the assembly cost. Then, a population consisting of a number of individuals evolves to the next generation through genetic operations of crossover and mutation based upon the fitness of the individuals. The population continues to repetitively evolve, and finally the fittest individual and its corresponding assembly sequence is found. Through case study for an electrical relay, the effectiveness of the proposed method is demonstrated. Also, the performance is evaluated by-comparing with those of previously presented approaches such as a neural-netowork-based method and a simulated annealing method.