Solving the e-commerce logistics problem using anti-predatory NIA

Abstract

E-commerce is expanding their roots in every business. Fast, efficient, reliable, timely delivery of goods and optimal transportation cost are the major challenges in e-commerce. To overcome these challenges, e-commerce companies are using a well-planned arrangement of warehouses and distribution centres (logistics network). This logistics network also reduces the operational cost and capital investment of an e-commerce company. This study proposes a novel solution to deal with e-commerce logistics problem (ECLP) using anti-predatory NIA (APNIA). The proposed approach is useful for identifying cities where warehouses and distribution centres can be established; and allocating the distribution centres to warehouse in order to reduce total cost of goods transportation. The proposed approach is also useful for predicting the number of warehouses to be established for optimal logistics network. The experimental evaluation reveals that the proposed method achieves 2.30% lower gap value and 20% more consistent optimal results as compared to the genetic algorithm.