Research Of Supplier Selection Problem Based On Improved Particle Swarm Optimization Algorithm

The problem of supplier selection is one of the important issues in supply chain management. Selecting advisable suppliers, for wholesalers in Linyi markets, can influence purchasing cost as well as marketing plan. Supplier selection problem, which is one of the nonlinear optimization issues, has become an academic point in logistics field. Scholars proposed many solutions to this problem, such as Analytic Hierarchy Process (AHP), Data Envelopment Analysis (DEA), etc. However, these methods' limitations are obvious,they only select specific supplier without optimizing purchase quantity and cost, so they can't reduce purchaser's cost. Particle Swarm Optimization Algorithm (PSO) can cover this shortage well, but related research is rare. This research improved typical PSO algorithm combining sub-swarmstrategy, simulated annealing algorithm and constraints handling mechanism, based on the general process of the PSO algorithm. This research also proposed the general steps of supplier selection solutions, which is adopting improved PSO algorithm.At first, this paper reviewed the current researches of supplier selection issues, analyzed and compared several index systems and methods of supplier selection, and then pointed out their problems. Secondly, this paper proposed the supplier selection index system and mathematical models, which are suitable for wholesalers in Linyi markets, based on the study of supplier selection index and the wholesale markets'feature in Linyi. Then, on the basis of analyzing the features of the typical PSO algorithm, this paper proposed an improved PSO algorithm to solve supplier selection issue, and tested it by simulation examples; At last, this paper designed a logistic optimization system based on SOA, according to the logistics industry and wholesale markets in Linyi, and give a method to implement supplier selection optimization function of the system.