An integrated online pick-to-sort order batching approach for managing frequent arrivals of B2B e-commerce orders under both fixed and variable time-window batching

Abstract

The emergence of e-commerce marketplace, especially the business-to-business (B2B) e-commerce sector, has created a vast market opportunity for retailers and logistics service providers (LSPs). However, facing the structural changes in B2B logistics orders, without any transformation of logistics operating process in distribution centres, LSPs are experiencing serious challenges in handling B2B e-commerce orders. In order for LSPs to grasp the market pie of the logistics and distribution sector of the e-commerce business through improving the core capability of handling B2B e-commerce order in their distribution centres, this paper proposes a novel approach for LSPs to systematically execute B2B order pre-processing so that the B2B e-commerce orders are better managed. An intelligent B2B order handling system (IOHS) is developed for efficient management of discrete, frequently arrived B2B e-commerce orders. By applying the “warehouse postponement” concept through the development of IOHS integrating cloud database management, fuzzy logic, and genetic algorithm approach, B2B order grouping solutions are effectively generated. A case study is conducted in a Hong Kong-based logistics service provider who handles outsourced B2B e-commerce orders, indicating the feasibility of the proposed solution to facilitate e-order fulfilment under both fixed and variable time-window batching settings in distribution centres. A significant improvement in terms of the throughput rate of handling B2B e-commerce order in the distribution centre is found, thereby increasing the satisfaction of buyers and sellers throughout the order handling and delivery process, as well as facilitating LSPs’ capability to manage a larger number of orders received from B2B e-commerce platform, given the greater product exposure of sellers in today’s B2B e-business.