Collaborative Optimization Of Vehicle Allocation And Fleet Size Based On Heterogeneous Vehicles

With the rapid development of economy and the acceleration of urbanization,higher requirements are put forward for the traditional logistics industry.Developing modern logistics industry and constructing efficient urban logistics distribution system have important theoretical and practical significance for the healthy development of cities and alleviating road congestion.Urban logistics distribution system takes information technology as its core,integrates all functions of logistics resources,optimizes and improves all realization processes,and improves the economic benefits of enterprises.In order to improve the logistics distribution system,it is the most effective way to optimize the transportation scheduling process,formulate reasonable transportation routes and reduce the cost of transportation logistics.The basic task of transportation and distribution is to rationally organize daily transportation production,scientifically organize vehicle flow adjustment and rationally formulate vehicle operation plan,so as to realize balanced transportation,tap transport potential and improve transport efficiency.In view of this,in order to improve the transportation efficiency of urban logistics distribution system and maximize the transportation capacity of transportation network,this paper optimizes the dispatch of transport vehicles scientifically and formulates reasonable distribution routes.The main research contents are as follows:Firstly,through consulting references,the definition,classification and components of vehicle routing problem are studied.The existing methods for solving vehicle routing problem are summarized.An integrated optimization problem of fleet size coordination and fleet station allocation based on multi-vehicle type and considering vehicle accessibility is studied.The vehicle accessibility and vehicle allocation on transportation road are considered.Under the conditions of loading restriction and so on,a mathematical programming model with the objective function of maximizing full-time revenue is established.Secondly,the advantages and disadvantages of existing heuristic algorithms are compared,and a hybrid simulated annealing heuristic algorithm is proposed by fusing the traditional greedy algorithm with simulated annealing algorithm.Finally,in order to verify whether the proposed method is suitable for solving this kind of problem,a hybrid simulated annealing heuristic algorithm is proposed.In order to solve the problem and whether it has higher efficiency,a comparative experiment of different scales is designed to compare it with the traditional CPEX solver for integer programming and the traditional greedy algorithm.The results show that the optimal solution can be obtained by using CPLEX solver with unlimited time,but the overall performance of the hybrid simulated annealing heuristic algorithm is better than that of the greedy algorithm,and the generated solution is closer to the optimal solution.At the same time,the solution obtained by hybrid simulated annealing heuristic algorithm is always better than CPLEX solver and greedy algorithm.Therefore,the hybrid simulated annealing heuristic algorithm has better performance.