Paper Title
A Decision Making Model for Dynamic-Demand Joint Replenishment Problem with Quantity Discounts and Transportation Cost

Abstract
In order to confront low cost competition in most industries, firms today often need to satisfy dynamic customer demand spontaneously. How to devise an appropriate decision making model for dynamic-demand joint replenishment problem is essential. In this study, a mixed integer programming (MIP) model is proposed first to minimize the total cost, which includes ordering cost, purchase cost, transportation cost and inventory holding cost, while satisfying various constraints in quantity discounts and transportation. Particle swarm optimization (PSO) is adopted next to solve the problem when it becomes too complicated to solve by the MIP. The PSO has an attribute to find solutions that are very close to the optimal ones in a short computational time. A case study of a bike manufacturer is presented to examine the practicality of the MIP and PSO models. Keywordsó Dynamic-demand Joint Replenishment Problem (DJRP); Quantity Discounts; Mixed Integer Programming (MIP); Particle Swarm Optimization (PSO).