Blockchain Assisted Multi-Objective Multi Time Window Cold Chain Intelligent Logistics Path Optimization

Abstract

Aiming at the dynamic demand path optimization problem of cold chain distribution, this paper combines the technical advantages of blockchain with the characteristics of cold chain path optimization problem on the basis of existing literature research. A multi-objective path optimization model with time window considering customer satisfaction is established, and then an example is designed and genetic algorithm (GA) is used to solve the above model. By comparing the indicators before and after optimization, it is concluded that the distribution cost of the distribution optimization scheme is low. Therefore, the combination of blockchain technology and cold chain distribution can effectively improve distribution efficiency, thereby reducing transportation costs and improving customer satisfaction. Finally, we completed the following work: 1) Summarized the research literature on vehicle routing problem (VRP) and cold chain logistics, and pointed out the current research trend. 2) The mathematical modeling of the actual logistics distribution problem is studied. Through the study of vehicle routing problem with time window (VRPTW) modeling method and multi-objective optimization theory, a multi-objective function is established and unified into cost objectives. The modeling elements are determined, and the multi-objective vehicle routing optimization model with time window is established by combining the objective function. Then the GA is determined as the algorithm for solving the model in this paper, and the algorithm flow is designed. 3) The algorithm parameters are set according to the actual distribution data of an enterprise, and then the effectiveness and optimization of the algorithm are tested to check the mutual constraints between the constraints of the model, as well as the optimization of the target value of the algorithm to solve the problem. The obtained path optimization scheme has more advantages than the original scheme.