Application of Improved Genetic Algorithm to Two-side Assembly Line Balancing

Abstract

Taking an automotive interior assembly line as the research object, a mathematic model is established which include the two-side effect as constraints. An improved genetic algorithm is presented to solve the two-side assembly line balancing problem. The encoding and decoding method is designed in the algorithm. The fitness function is constructed, the initial population selection method and the choice mechanism is determined to fit the algorithm. The crossover and mutation method of the population is presented. Furthermore, the numerical result shows that the reduction of the number of workstation and a better balance rate can be obtained by proposed improved genetic algorithm which is superior to the normal one.