An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes
Document Type
Article
Publication Date
8-1-2023
Abstract
Shortest path problems are encountered in many engineering applications, e.g., intelligent transportation, robot path planning, and smart logistics. The environmental changes as sensed and transmitted via the Internet of Things make the shortest path change frequently, thus posing ever-increasing difficulty for traditional methods to meet the real-time requirements of many applications. Therefore, developing more efficient solutions has become particularly important. This paper presents an improved discrete Jaya algorithm (IDJaya) to solve the shortest path problem. A local search operation is applied to expand the scope of solution exploration and improve solution quality. The time complexity of IDJaya is analyzed. Experiments are carried out on seven real road networks and dense graphs in transportation-related processes. IDJaya is compared with the Dijkstra and ant colony optimization (ACO) algorithms. The results verify the superiority of the IDJaya over its peers. It can thus be well utilized to meet real-time application requirements.
Identifier
85168874301 (Scopus)
Publication Title
Processes
External Full Text Location
https://doi.org/10.3390/pr11082447
e-ISSN
22279717
Issue
8
Volume
11
Recommended Citation
Wang, Ren; Zhou, Mengchu; Wang, Jinglin; and Gao, Kaizhou, "An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes" (2023). Faculty Publications. 1541.
https://digitalcommons.njit.edu/fac_pubs/1541