An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes

Shortest path problems are encountered in many engineering applications, e.g., intelligent transportation, robot planning, and smart logistics. The environmental changes as sensed transmitted via the Internet of Things make shortest change frequently, thus posing ever-increasing difficulty for traditional methods to meet real-time requirements applications. Therefore, developing more efficient solutions has become particularly important. This paper presents an improved discrete Jaya algorithm (IDJaya) solve problem. A local search operation is applied expand scope solution exploration improve quality. time complexity IDJaya analyzed. Experiments carried out on seven real road networks dense graphs transportation-related processes. compared with Dijkstra ant colony optimization (ACO) algorithms. results verify superiority over its peers. It can be well utilized application requirements.