Optimization of delivery routes for takeout under time-varying road networks

Food delivery has emerged as a crucial aspect of the dining experience, driven by the proliferation of the Internet and the expansion of the catering industry. Delivery times have become a significant factor affecting customer satisfaction. However, the inherent unpredictability of the delivery process can lead to delays, which in turn can diminish customer contentment with the delivery platform if the actual delivery time surpasses the promised time frame. Consequently, this paper addresses the optimization of delivery routes for couriers who encounter uncertainty during their deliveries. To quantify the randomness of the distribution process, the study introduces a random influence factor that accounts for road obstacles and weather conditions. Different coefficients for road obstruction and weather influence are assigned to various road sections and delivery times to accommodate the stochastic nature of static road segments. Based on this, a takeout delivery optimization model that incorporates stochastic elements is formulated. This model is designed to effectively optimize the delivery plan, achieving a balance between delivery costs and customer satisfaction. The proposed model is solved using a taboo search algorithm. The effectiveness of the delivery model and algorithm is validated through simulations that compare the performance of the delivery route model under different weather conditions and road obstacle coefficients. The objective of this study is to assist delivery couriers in planning their routes in a rational and scientific manner to enhance delivery efficiency while managing the uncertainty of the road network. Additionally, the research aims to provide practical recommendations and solutions to reduce delivery operation costs and improve customer satisfaction.