Research on Random Mixed-model Two-sided Assembly Line Balancing Using Genetic Algorithm

This paper presents a new mathematical for random mixed-model two-sided assembly line balancing. To minimize the cycle time of random mixed-model two-sided assembly line with the given number of workstation, the random mixed-model two-sided assembly line balancing problem of type II is studied. The influence of random factors on assembly line was convertedinto process time influence in the paper. Combined with random changes in product demand of different product, the united comprehensive process time was worked outby the method of weighted average. According to the comprehensive process time, the processeswere rearrangedto different workstations in the paper. To minimize the cycle time which as the objectives of the mathematical programming model, with constraints of process priorities, operational orientation and others, the genetic algorithms is used to work out the mathematical model. An instance of mixed-model two-sided automobile assembly line was given, which was optimized by the algorithm for optimization and compared the results of optimization before and after. The results verify the effectiveness of the algorithm for solving mixed-model sided assembly line balancing problem.