Application of Improved Dijkstra Algorithm in Coastal Tourism Route Planning

• Published in: Journal of coastal research Vol. 106; no. sp1; pp. 251 - 254
• Main Author: Chen, Yijing
• Format: Journal Article
• Language: English
• Published: Fort Lauderdale Coastal Education and Research Foundation 01.06.2020; Allen Press Publishing; Allen Press Inc
• Subjects: Algorithms; binary sort tree; COASTAL ECONOMY AND DEVELOPMENT; Coastal engineering; Coastal inlets; Coastal research; Coastal tourism; Coasts; Computer science; Dijkstra's algorithm; Embedded GIS; Geographic information systems; Geographical information systems; Graphs; Industrial development; Mathematical analysis; Network analysis; Nodes; Route planning; shortest path; Shortest-path problems; Storage; Sustainable development; Tourism
• ISSN: 0749-0208; 1551-5036
• DOI: 10.2112/SI106-059.1

Chen, Y., 2020. Application of improved Dijkstra algorithm in coastal tourism route planning. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 251–254. Coconut Creek (Florida), ISSN 0749-0208. With the development of computer science and geographic information science, there are more and more applications for GIS. Shortest path analysis is a key issue in GIS geographic network analysis. One of the classical algorithms for calculating the shortest path is the Dijkstra algorithm, which is used in many projects to solve the shortest path problem. However, when the traditional Dijkstra algorithm solves the shortest path between nodes, a large number of nodes outside the identified nodes are calculated, which affects the speed of the algorithm. The Dijkstra algorithm is a classical algorithm for solving the shortest path in the embedded GIS system. By analyzing the Dijkstra algorithm, changing the storage structure, and examining graphing methods, the binary ordering tree algorithm based on the rectangular restricted area reduces the memory storage space. Shortening the query time requires optimizing the shortest path calculation process; the actual data test also shows the effectiveness of the algorithm.