Abstract：In the actual distribution process, to solve the problem of traffic congestion by traffic accidents, peak hours of commuting and traffic restrictions,and to ensure the results of multitemperature codistribution path optimization more consistent with actual situation, the multitemperature codistribution optimization model of traffic congestion was proposed based on traffic congestion. Compared to the traditional multitemperature coproperty path optimization model, the proposed model was more consistent with the actual transportation situation. To solve the path optimization problem with NPhard problem, a random adaptive genetic algorithm was used to achieve the optimal distribution path with the shortest path and the lowest total cost for the total optimization cost. The results show that comparing with genetic algorithm and solving with Cplex, the results are closed,and the proposed algorithm is faster, which is more suitable for largescale solution. The results of example analysis illuminate that compared with the path optimization without considering the congestion situation, the transportation cost of the path optimization with considering congestion situation is decreased by 16.74％.
2019, Vol. 40 
