Membrane Computing Multi Particle Swarm Optimization And Its Application

Since the founding of new China, especially with the process of the reform and opening up, the development of Chinese manufacturing industry has been sustained and fast. Therefore, a multitudinous and independent industrial system has been built, which vigorously promoted the process of the industrialization and modernization and significantly enhanced overall national strength. However, compared with the world's advanced level, Chinese manufacturing industry is still large but not strong. In addition,there is an obvious gap of the ability of independent innovation, the efficiency of resource,the level of industrial structure, the degree of technological information, quality and efficiency and so on. Thus, reaching the goal of upgrade, leaps and bounds develop is urgent and arduous. To improve the quality of product and the degree of manufacturing management and achieve strategic transformation and high-end manufacturing, in this paper, it introduces an optimization algorithm that combines particle swarm optimization with membrane computing to solve complex optimization problems that faced with during the actual production design.Firstly, considering the problems that particle swarm optimization algorithm is easy to fall into local excellent situations and the rate of convergence at later evolution stage is slow, an optimization is proposed. Through the method that puts six kind of particle swarm algorithms, original PSO?PSO?MPSO?EPSO?MFPSO?TFPSO, which have different advantages into six membranes separately. At early stage, each monolayer membrane grows up based on their own searching mechanism to play the advantages of each algorithm. At late stage, each algorithm in the membranes exchange a variety of energy with each other, so that the membrane of the most suitable solution to this problem absorbs others nutrients for growing up and dissolves the membranes of poor searching ability gradually to look for the optimal solution.Secondly, the optimization algorithm presented in this paper and other algorithms in the membranes are compared through test functions. Then the population diversity of the new optimization algorithm is tested. in addition, compared with the population diversityof Genetic algorithm ? fish-swarm algorithm and some other algorithms of membrane computing combined with particle swarm optimization.Thirdly, based on the T-S fault tree theory, the analysis method of reliability is introduced to the optimization algorithm presented in this paper to establish reliability optimization model, which is used for optimizing the reliability of series system, bridge system and the actual production system as well.Finally, through constructing problem solving model, the optimization algorithm presented in this paper is applied to hybrid flow-shop scheduling problem, the practical application of shop scheduling problem about automotive engine and hydraulic valve block.