Research And Optimization On Complex Assembly Line Balancing Problem

In the manufacturing industry, assembly line is an important form of production organizing. Enhancing assembling efficiency will accelerate production and bring apparent economic benefits.With the development of science and technology, the feature of assembly line is updating. In order to fit the market and the various needs of customers,mixed-model assembly line is widely used. Compared to the simple assembly line, the mixed-model one is much more complex.In this thesis, the development of assembly line and its layout features in the process of manufacturing is introduced first. Base on the simple assembly line, mixed-model assembly line is mainly discussed. Models of the balancing problem and the products sequencing problem are respectively presented, which may be instructive for production management. The workstation model has taken number and load equilibrium of workstation into consideration to optimize the task assignments,and the products sequencing model has taken the times of production switch,and the difference between ideal and real outputs into consideration to connect the problem to the load of workstations.Different algorithms for the two objections are introduced. In the research of genetic algorithm,improvements are made to enhance the performance of the solutions.For the balancing problem, workstation ID is used for encoding, and decoding-arrangement for the genetic operators.For the sequencing problem, fitness function is transformed based on SA, in order to enhance search efficiency.The algorithms are realized through real engine production data, the simulation results show that the algorithms in this thesis can solve the mixed-model assembly line balancing problem effectively.