Fuzzy Scheduling of Logistics Production and Distribution under Uncertain Environments using Particle Swarm Optimization

In this paper we attempt to integrate production scheduling and distribution routing problems to minimize the total cost of the supply chain under uncertain environments. The particle swarm optimization method is used to select the location of the distribution center, combining it with the tabu search algorithm to solve vehicle distribution route problem. Especially, the location of each particle is encoded as a floating point number. Each particle consists of a two row matrix, the first row represents the location of distribution center and the second row the link between distribution center and customer. The experiment results show that this scheme can solve production-distribution problems in the global sense efficiently. In the future, convergence speed and accuracy based on particle swarm optimization will be studied to reduce running time of the proposed algorithm, and its performance will be compared with other intelligent computing techniques. KeywordsLogistics Production-distribution; Particle Swarm Optimization; Fuzzy Scheduling, Uncertain Environment.