A novel vehicle path planning method for freight enterprises considering environmental regulation

Abstract

In the paper of vehicle path planning, it is necessary to factor in both governmental regulation policies and enterprise regulation investments. In this paper, a novel method for vehicle path planning is investigated, which incorporates environmental regulation to determine the transportation path, driver, and vehicle type in a joint manner. The mathematical formulation of the investment decisions related to internal self-regulation is provided, considering four external regulation policies. To address the challenges posed by the multidimensional, discrete, and non-linearity model, an improved dynamic disaster genetic algorithm with elite strategy (ED-GA) is proposed. The numerical results demonstrate the effectiveness of the ED-GA in solving large-scale path planning problems, considering both effectiveness and running time. Moreover, this paper analyzes the variations in internal environmental regulation and external environmental regulation, elucidating the impact of different degrees of internal regulation and exploring the applicability of various external regulations. The proposed method is particularly relevant for freight enterprises that possess their own vehicles and are committed to investing in emission reduction. It offers valuable guidance for decision-making and management in low carbon vehicle path planning.