An improved particle swarm optimization algorithm in selection of e-commerce distribution center

Under the influence of COVID-19, the efficiency of e-commerce distribution in public health emergencies has become the key to ensuring people’s normal lives. With the development of e-commerce, the location of distribution center is becoming more and more important, which is related to the healthy and long-term development of e-commerce. However, the traditional location efficiency is low, which cannot play an immediate role in the development of e-commerce. This paper combines weiszfeld algorithm, improves particle swarm optimization algorithm, improves the operation efficiency and location accuracy, and finally gets a relatively satisfactory result. Results data analysis shows that the improvement and integration of the algorithm is reasonable and effective. This method has important reference value for e-commerce location.

Revised Weighted Fuzzy C-Means and Fortified Weiszfeld Hybrid Method for Uncapacitated Multi-Facility Location Problems

In this article, a hybrid method is proposed to solve the uncapacitated planar multi-facility location problems. The new hybrid method consists of a combination of the Revised Weighted Fuzzy C-Means (RWFCM) algorithm proposed by Esnaf and Küçükdeniz (2013) and the Fortified Weiszfeld algorithm developed by Drezner (2015). The cluster centers and the cluster assignments of the RWFCM are fed into the Fortified Weiszfeld Algorithm separately for each cluster and facility-customer allocations are determined. The proposed approach is benchmarked on sample datasets from the facility location literature. Results of the proposed hybrid method show that the newly proposed sequentially-run method achieves better results when compared against the benchmark methods. This paper is a pioneer study of the hybrid use of Revised Weighted Fuzzy C-Means and Fortified Weiszfeld algorithms.