Research On Vehicle Routing Problem Based On Ant Colony Algorithm In Logistics System

With the development of technology and social progress, the logistics is another source of enterprise profit outside of the production area, but also the core power of market competitive. Vehicle routing problem (VRP) is one of the research hotspots in the field of operations research, applied mathematics and computer, its purpose is to design reasonable routes for the vehicles in order to achieve the purpose of reducing the transport cost. Logistics distribution vehicle scheduling problem of path optimization is a typical NP-hard hard problem in combinatorial optimization, when the scale of the problem is large, the computing time needed for the solution will increase as the problem size increases, we will be difficult to get the exact solution of the problem. Therefore, the present method of logistics distribution vehicle scheduling problem in path optimization is the use of heuristic algorithm, In this regard, this paper mainly aims at the logistics vehicle scheduling problem of path optimization in different constraint conditions, we improve Ant colony algorithm in three ways, and the improved algorithms are respectively by simulation to verify the effectiveness of the algorithm.At first, In view of problem which the ant colony algorithm in solving VRPTW easily plunged into local optimum, this paper defines a new ant transition probability of saving ideas, and uses the Pareto optimal solution set of global pheromone updating rule, and puts forward a kind of improved Pareto ant colony algorithm (PACA). Through the simulation experiments show that IPACA improved the global search ability of AC A, effectively avoid the algorithm falls into local optimum, and reduces the total distribution cost (distance), so as to verify the effectiveness of the proposed algorithm.Secondly, for a single distribution center with time windows, vehicle routing problem of logistics will appear interference events such as changes of customer time windows and changes in demand.Once more, this paper mixes the Adaptive Memory Program algorithm and the ant colony algorithm, then proposes Adaptive Memory Programing for Ant Colony Algorithm. And apply the algorithm to Vehicle Routing Problem with Simultaneous Delivery and Pick-up.Finally, this paper makes a summary of the full text, and prospects the further research work.