Research on "one-to-many" Vehicle and Cargo Matching Optimization Problem based on Improved Genetic Algorithm

Abstract

The matching relationship between vehicles and cargo affects the merits of the transportation program, so the vehicles and cargo arrangements reasonable matching program is very necessary. Vehicle and cargo matching refers to obtaining the optimal allocation plan through intelligent matching under the condition of known certain vehicle and cargo information, so as to realize the optimization of cost and time single-objective and dual-objective. When solving the problem of vehicle and cargo matching, pay attention to the impact of vehicle and cargo information on the results. Therefore, this article comprehensively considers the effect of different attributes of vehicles and cargo on the matching scheme, and proposes a "one-to-many" vehicle and cargo matching model based on the attributes of vehicles and cargo. The difference between this article and the general “one-to-many” vehicle and cargo matching scenario is that it provides feasible cargo matching schemes for multiple types and multiple vehicles at the same time, in order to get the highest overall profit under the condition of meeting the weight limit of each vehicle. An improved Genetic algorithm is used to solve the problem, and the greedy operator is introduced to screen the initial results. The results show that this method can effectively increase the full-load rate of mainline vehicles and rationalize the allocation of vehicle and cargo resources.