Path planning optimization with actual road conditions by using meta-heuristic algorithms

Abstract

Timely delivery is the core goal of logistics business and directly affects customer satisfaction and loyalty. However, uncertain factors such as road damage, traffic congestion and traffic accidents often make it impossible to deliver on time by the shortest path. To this end, this paper proposes a path optimization algorithm based on actual road constraints and with the shortest driving time as the goal. Different from the traditional traveling salesman problem (TSP), this study minimizes the transportation time based on the open-loop TSP model. By constructing a time cost function considering road conditions and introducing three meta-heuristic algorithms for route optimization. Experimental results show that the OriginalABC algorithm performs best among multiple schemes with the lowest average time cost.