Open AccessShortest path planning for mobile chargers
Author(s) -
Yi Huang,
Xiaojian Shen,
Jiaqi Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1861/1/012104
Subject(s) - shortest path problem , genetic algorithm , wireless sensor network , computer science , path (computing) , constrained shortest path first , node (physics) , wireless , real time computing , mathematical optimization , k shortest path routing , algorithm , computer network , mathematics , engineering , telecommunications , machine learning , theoretical computer science , graph , structural engineering
This paper studies the shortest path that a mobile charger should travel when charging a wireless rechargeable sensor network. Under the condition that the latitude and longitude of each node in the wireless rechargeable sensor network are known, we combine the actual working conditions of the mobile charger to establish a TSP problem model and use two improved modern optimization algorithms and three common optimization algorithms to solve. By comparing the results, we conclude that the improved genetic algorithm can obtain the shortest path length of 11485 m with the least number of iterations. The improved genetic algorithm has better applicability to the problem in this background.