The Multi-Objective Optimization Of Facility Layout Based On Particle Swarm Optimization Algorithm

The problem of facility layout has been an issue for a long time in the industrial society. The early environment of facility layout is relatively stable so that the structure of facility layout is also simple, which means the enterprise can meet the market demand just during its life period. While the late-development advantage of China is being used up, the situation of slowing development should be faced in all fields, and as the role of basement for the development. The industry filed is the first to be faced by the situation. In this background, the purpose of this paper is to solve the problem of facility layout.Firstly the theory of facility layout was stated in this paper which includes the structure of the facility planning theory. Then the theory of Systematic Layout Planning(SLP) was analyzed comprehensively, which made the disadvantages of it be obvious.The traditional way to solve the facility problem is mature and has been a system.Though qualitative analysis is adopt in the theory,the effect based on the whole design is more considered because of the systematicness of the theory, which actually has reduced the flexibility without consideration of specific target.The strategy of this paper is that facility layout is optimized based on the basic process of SLP.Secondly, frequently-used algorithm was introduced, concluding the advantages or disadvantages of different algorithm, and then PSO is adopted. Improved PSO was proposed in the paper to solve Multi-Objective Optimization(MOP) problem in facility layout problem. The algorithm was based on the strategy that the historical best position updates the velocity of particle. With Learning probability and Elite probabilityproposed,the former of which determines the object, and the latter of which determines the dimension, traditional object and dimension was avoided, making the algorithm more practical.Then the model to fulfill optimization was set based on the two direct factors for the profit of the company. To make the point more clear and convincing, Genetic Algorithm(GA) was also adopted in the case.the design was optimized based on different algorithm, which made the comparison more scientific.The disadvantage of SLP was avoided in the method of study of this paper through the combination with the theory of Multi-Objective Optimization Problem, and PSO was taken use of in this paper. The conclusion we draw in this paper could be applied to in different fields.