基于混合蚁群算法的冷链物流配送路径优化研究

基于绿色物流发展理念，为企业寻求经济与环境达到双赢的局面，本研究将节能减排转化为绿色成本，融入路径优化问题中，建立以总成本最小为研究目标的冷链物流路径优化数学模型。针对蚁群算法初始阶段由于信息素不足导致收敛速度慢的问题，将A*算法与蚁群算法相结合，利用A*算法的全局收敛性和蚁群算法的正反馈性构造了一种混合蚁群算法。通过对实例进行仿真优化与对比分析，验证了模型和算法的有效性。

Research on Cold Chain Logistics Distribution Path Optimization Based on Hybrid Ant Colony Algorithm

With the development of society, consumer demand for fresh green food is increasing.In order to meet market demand and improve their competitiveness, cold chain logistics enterprises constantly expand the number of vehicles in the transportation process, however, their operating costs also increases.For the development of modern cold chain logistics enterprises,high costs have become the biggest resistance to their development. Meanwhile, with the implementation of the concept of green logistics in China,enterprises will simultaneously face the dual pressures of economy and environment.In response to this problem, this paper intends to find a distribution strategy for cold chain logistics enterprises,so that enterprises can achieve a win-win situation of economy and environment. Therefore,based on the concept of green logistics, energy conservation and emission reduction are converted into green cost,and a mathematical model is established with fixed cost, green cost,refrigeration cost, cargo damage cost and soft time window penalty cost, and the minimum total costs as the research goal. The vehicle routing problem (VRP) is an NP-hard problem and cannot be solved by an precise algorithm. In this paper,a hybrid ant colony algorithm is proposed to solve the vehicle path model of cold chain logistics.Aiming at the problem of slow convergence due to insufficient pheromone in the initial stage of ant colony algorithm, the A* algorithm is used to find the optimal solution, and initial pheromone of the corresponding path is assigned the value λτ_c,(λ>1). The initial pheromone of other paths is assigned the value τ_c.The purpose of shortening the convergence time of the ant colony algorithm and reducing the convergence time is achieved.At the same time,heuristic factors and transfer probability are modified according to the research content in this paper to make the mixed ant colony algorithm more suitable the problem to be studied in this paper. The data provided by a cold chain logistics company in Xi'an are used to verify the effectiveness of the model and algorithm. The results show that the model and algorithm of this paper can provide an effective distribution strategy for cold chain logistics enterprises, this strategy can reduce costs for logistics com-panies and facilitate business development. Furthermore, to verify the validity of the algorithm, after the algorithm comparison, the ant colony algorithm that initializes the pheromone can effectively reduce the convergence time.The hybrid ant colony algorithm can effectively reduce the distribution cost of the enterprise compared with the basic ant colony algorithm and the A* algorithm. In summary, the model and algorithm of this paper can provide method support for logistics enterprise's distribution activity optimization.