More Constrained Dynamic Path Planning Research And Application

With economic development, it was found that more and more cars on the road, but the traffic is getting blocked, people travel gradually became headache, driving must use a GPS Navigation System has become a common phenomenon,vehicle congestion is not a very serious case, a simple navigation system can meet the needs of the public, however, as more and more vehicles, the road congestion is more serious, the only existing path planning system planning the shortest routegradually unable to meet the needs of people, It is hoped that one can consider the system of planning the path of the various constraints information, take into account the current traffic conditions in the path planning system, while not a static path. With such demand, we in this paper, we mainly do two aspects, one of:dynamic path planning algorithm for multi-constraint optimization; Second:we combine the supply chain management system, multi-constraint dynamic path planning the algorithm is applied to supply chain management system, design and implementation of the entire system.In the multi-constraint dynamic path planning, select the classic algorithms in the existing path search algorithm Dijkstra algorithm and A*algorithm, by comparing the real-time nature of these two algorithms implementation process and the execution characteristics and supply chain systems-year-old algorithm requirements, and through selected test cases selected to optimize the A*algorithm, the accuracy of comparison of the three algorithms in the search results, search computation time and the comparison of the three aspects of access nodes to elect optimized A*algorithm as a multi-constrained path search algorithm. Later, according to the user in the process of using the demand for multi-constrained path, we will optimize the A*algorithm with the multi-constrained optimal path problem combining vector through the design limits the right to strike the path of least limit weight vector, strike to meet the multiple constraints optimal path problem., In order to prevent the occurrence of the phenomenon of "congestion drift in the path planning process, use the Kpath search strategy, planning path is not only the optimal path, as well as sub-optimal, and again excellent path, effectively preventing occurred crowded drift. In supply chain management system, we first analyzed the supply chain management model to analyze the most core of supply chain logistics and transport links, the establishment of multi-constraint-based dynamic path planning system. In the system, combined with the MIS and GIS technology, is designed on the basis of the full analysis of the demand for supply chain management system design, system architecture, and in different roles to be different permissions. Use of space data, combined with WebGIS framework for spatial data management, and client through the design of simple and friendly interface, easy for users to select the beginning and the end of planning routes, and planning on the client. On the server side, we choose a different search algorithm to achieve a Dijkstra algorithm and optimized MCOP algorithm, dynamic path planning of multi-constraint optimization function to achieve more practical value in the supply chain management, logistics and transport.