Abstract
In this highly competitive and low-profit marketing environment, the challenge that chain-store resale industry face is how to implement inventory management techniques so that cost down is possible and quality of customer service can be improved simultaneously to broaden market share. In this study, a transshipment approach is proposed by selecting several retail stores not only served as a warehouse for high-end, low-volume products but also are responsible for inventory and delivering to share and lower their risk to minimize overall system costs. However, locations of warehouse to products must be considered along with inventory management and transshipment arrangements to achieve their maximum performance for the whole system. To solve this problem, a transshipment model, proposed in this research, is formulated by an integer nonlinear programming methodology. And two efficient local search algorithms based on Simulated Annealing and Tabu search are developed on integer nonlinear programming, instead of using traditional mathematical approaches, having difficulties in solving these problems with time-consuming drawback and restrictions on large scale. Study shows that both algorithms are efficient, obtaining optimal solutions on small-sized problems. In this research, computational results with up to 200 retail stores to evaluate the performance with these two algorithms in large scale are also presented. And based on the acquisition of data, Tabu Search outperforms Simulated Annealing either in time-consuming or calculating quality.