Abstract
With the rapid growth of China’s logistics market, one of the most important research issues is designing a large-scale distribution network. The question of large-scale distribution network design is also becoming central to globalization supply chain management. Distribution network design can be considered as two parts: locating manufacturing plants and distribution centers, and determine the best strategy for communications between manufacturing plants and distribution centers. In this article, we study capacitated facility location in large-scale networks and its application to distribution network design. In a distribution network, each distribution center or client has associated with a demand, and each plant or facility has a capacity that specifies the maximum service the plant can provide to its distribution centers. Our aim is to select a subset of plants such that the demand requirement of each distribution center is satisfied, the plants capacities are not violated, and the total cost, including plant operating cost and service cost, which is usually based on the metric distance between plants and distribution centers, is minimized. The key challenge is that the computational complexity grows exponentially in the network size. We refer to the dynamic programming algorithm from Kao et al. [18] (2011) to build a distribution network, and we provide local swap techniques to better approximate the optimal assignment in the distribution network. Based on the dynamic programming algorithm and local swap techniques, we present a fast and accurate approximation approach to the large-scale distribution network design. In addition, we build a graphical user interface (GUI) system and the proposed system demonstrates its practical usefulness. Our GUI system can approximate the optimum within a constant ratio, and the computation time cost of our algorithm is much faster than that of Lingo. Keywords: Distribution network; facility location; large-scale network.