Assembly sequence planning optimization for aircraft assembly based on GA

Among Cut-set algorithm based assembly sequence planning approaches, there is a problem that number of assembly sequence increases exponentially along with number of components increase which will lead to combinatorial explosion. To solve this problem, an approach of assembly sequence planning optimization for aircraft assembly based on Genetic Algorithm (GA) and fuzzy set theory was presented. Firstly, gene-group was used to express assembly information of a component. In assembly, gene-groups of all parts combined to form a chromosome, which was used to express one assembly sequence. Then, fitness function was built according to fuzzy set theory and assembly sequence was evaluated and optimized. Finally, an improved genetic algorithm for assembly sequence planning was put forward. Successful application of this approach was validated by sequence optimization of a specific aircraft wing.