Optimal Route Crowd-Shipping System for Sustainable Rapid Delivery: Algorithm, Simulation, and Feasibility Evaluation

Abstract

Delivery systems are ubiquitous in today’s economy. However, those systems usually operate through purpose-built vehicles, which are inefficient, expensive, and highly harmful to the environment. We propose an optimal route crowd-shipping (OR-CS) system, a delivery service based on crowd transportation. The OR-CS system utilizes service points (SPs) and occasional couriers (OCs) to transfer deliveries. Senders drop packages at SPs, while receivers collect them from different SPs. The system is based on a new algorithm that assigns to each package an optimal route. The route is chosen individually for the package and is personally tailored according to the sender’s preferences and to the predefined routes of the OCs. To assess the real-life feasibility of the system, we developed a general simulator that emulates a city environment with authentic service points specifically selected based on desired attributes. The routes of OCs and the origins and destinations of packages were generated using a random process that differed between simulations. The results indicate that the system can be implemented and utilized. In addition, it yields positive results when the number of OCs surpasses a minimum threshold, which is feasible in most cities, given existing traffic loads. By adopting OR-CS, we can expect lowered delivery costs, reduced traffic congestion, and enhanced environmental sustainability.

An Intelligent Connected Vehicle Material Distribution Route Model Based on k-Center Spatial Cellular Clustering and an Improved Cockroach Optimization Algorithm

“…From the perspective of cost saving and an energy consumption reduction, the process of intelligent connected vehicles starting from a distribution center E (i) , transporting materials to a d number of distribution points D (i) , and finally returning to the distribution center E (i) , requires minimizing route costs. Based on the geographical constraints, the starting point of the intelligent connected vehicle distribution route is E (i) , the middle points are the d number of distribution points D (i) , and the terminal point is E (i) , which forms a complete closed interval [33,34]. Based on the principle of distribution route modeling and the characteristics of the distribution route, it can be concluded that vehicles depart from the distribution center, pass through several target distribution points, and finally return to the distribution center.…”