Research On Balancing Optimization Of Mixed-Model Assembly Line Based On Multi-Objective

With the advantage of being able to mix production of multiple products at the same time mixed-mo del assembly line have been widely used in today's manufacturing companies.Companies c an pro vide c us tomers with perso nalize d and divers ifie d customized products.However,when a company produces orders for different customers,the variety and quantity of products will change accordingly.The original assembly line is no longer suitable for the production of new orders.The company needs to redesign new mixed-model assembly line.Due to the differences in the assembly time of different products and the uncertainty of the assembly process,the balance of mixed-model assembly lines is more complex than that of single-type assembly lines.How does the company ensure the shortest time for converting,the minimum number of equipment used,the highest assembly efficiency,and the total cost of labor become the urgent problem that enterprises urgently need to solve under the condition of ensuring timely delivery of orders.By summarizeing and analyzing the current research status of mixed-model assembly line balancing problem at home and abroad,and combines the practical problems of difficult balance of mixed-model assembly line in enterprises to minimize the number of working sites,minimize the actual production cycle,balance the load among work sites,and The task of instantaneous load balancing and minimizing the total cost of labor as optimization objectives establishes a multi-objective optimization mathematical model.Combining the advantages of genetic algorithm and simulated annealing algorithm,a hybrid ge netic algorithm was designed as a solutio n to the balance problem of mixed-model assembly line.The genetic algorithm uses the local optimization ability of the simulated annealing algorithm to perform a local search on its better solution to make it jump out of the local optimum.Simultaneously,the simulated annealing algorithm utilizes the global optimization ability of the genetic algorithm to implement a parallel search of multiple solutions,improving the ability to search the global solution space.The feasibili ty of the algorithm is verified by an example analysis.In addition,the optimization of the assembly line balance problem in the final assembly shop of Changchun FAW Liberation Co.,Ltd.truck factory was optimized.This paper verifies the practicability of the hybrid genetic algorithm proposed in this paper to solve the multi-objective mixed-model assembly line balancing problem.Finally,this paprer use Flexsim three-dimensional simulation software to establish the simulation model before and after the optimization of the truck assembly line of FAW Jiefang.Through the analysis of the simulation results,it shows that the mathematical model proposed in this paper can achieve simultaneous optimization of multiple objectives of the mixed flow assembly line,and the designed hybrid genetic algorithm is effective in solving practical problems of mixed model assembly line balancing.