Meal delivery routing optimization with order allocation strategy based on transfer stations for instant logistics services

Abstract

The rapid development of instant logistics services has brought not only convenience to people's life but also a great challenge to traffic management. Due to the limited delivery range of instant delivery systems, customers are usually recommended the meals nearby or pay much higher delivery fees for long‐distance delivery. This study proposes a novel order splitting strategy based on transfer stations for long‐distance meal orders to satisfy the diverse customer demands. The meal delivery routing problem is addressed with an order allocation strategy based on transfer stations through developing a three‐stage modelling framework consisting of order combination, splitting and delivery routing for the online‐to‐offline instant logistics services. Normal meal orders are combined by the DBSCAN algorithm, and the cross‐regional long‐distance orders are split by transfer stations. Based on order combination and splitting, a mixed integer programming model is constructed for the meal delivery routing problem and solved by the adaptive large neighbourhood search algorithm. The proposed algorithm converges quickly for the tested instances constructed based on real platform data. The proposed order allocation strategy can expand the delivery scopes of couriers effectively, stimulate more potential orders and guarantee the timeliness of meal delivery.

Order Distribution and Routing Optimization for Takeout Delivery under Drone–Rider Joint Delivery Mode

“…The spatiotemporal distance measurement method was introduced, the routing optimization model was established with the goal of minimizing the cost of meal delivery, and a two-stage heuristic algorithm was designed to solve it. Li et al [44] studied a remote takeout order splitting strategy based on transit stations, established a mixed integer programming model for the takeout delivery route problem, and solved it using an adaptive large neighborhood search algorithm.…”

Optimal Strategies of the Online-to-Offline Instant Delivery Service of Grocery Retailers

“…Xuping et al (2019) researched the impact of the distribution range of O2O fresh food experience stores on costs and benefits. Both Li et al (2022) and Du et al (2022) studied the delivery range through the model. Du, Fun & Sun (2023) examines the phenomenon of delivery delays in the takeout industry, where some firms offer delay compensation policies to consumers, which is closely related to the delivery range, which is an important factor affecting delivery quality.…”

“…Due to the limited delivery range of the instant delivery system, customers are usually recommended to dine nearby or pay a higher delivery fee for long-distance delivery. The order allocation strategy proposed by Li et al (2022) can effectively expand the delivery range of the courier, stimulate more potential orders, and ensure the timeliness of meal delivery. Regarding the starting price.…”