Multi-objective optimization of truck-drone joint delivery with restricted areas

Abstract

Aiming at the problems of "last mile" cost, low customer value, and poor logistics due to regional restrictions, a truck-drone joint delivery model is proposed, which takes customer value and customer satisfaction as measurement factors under regional restrictions, in which drones can visit multiple customers in one flight. Combined with the constraints such as customer time window, unmanned aerial vehicle (UAV) load and endurance limit, vehicle load, etc., a multi-objective truck-drone joint distribution route optimization mathematical model is established to minimize cost, maximize customer value and customer satisfaction. According to the characteristics of the model, an improved non-dominated sorting genetic algorithm III (NSGA-III) is designed to solve the model, and the effectiveness of the algorithm and model is verified by using large, medium and small calculation models selected from the classical Sioux-Falls traffic network and Eastern-Massachusetts road network. The results show that considering customer value and customer satisfaction increases the cost by about 6.95%, but customer value and customer satisfaction increase significantly by 37.52% and 13.1%, respectively. This is very beneficial for enterprises to maintain quality customers and improve customer loyalty, and helps enterprises achieve sustainable development.

Keywords

• transportation planning and management
• vehicle routing problem
• joint distribution
• regional restriction
• customer value
• customer satisfaction
• improved nsga-iii