Mobile Charger Planning for Wireless Rechargeable Sensor Network Based on Ant Colony Optimization

Fan Hsun Tseng, Hsin Hung Cho, Chin Feng Lai

研究成果: Conference contribution

摘要

In order to provide a more flexible wireless rechargeable sensor network, a charger and a self-propelled vehicle are integrated into one vehicle in recent years. The path selection problem of mobile chargers can be formulated as the well-known travelling salesman problem. Therefore, metaheuristic algorithms can be applied to solve the planning problem of mobile chargers. Some researches presented planning methods based on the Simulated Annealing (SA) and Tabu Search (TS) algorithms but the results are not satisfied. In this paper, we not only design a novel encoding approach but also the fitness function for proposing an efficient planning algorithm based on the Ant Colony Optimization (ACO) algorithm. Simulation results show that the proposed ACO-based algorithm achieves a shorter planning path for a longer network lifetime compared with that generated by the SA and TS algorithms.

原文English
主出版物標題Advances in Computer Science and Ubiquitous Computing - CSA-CUTE 2019
編輯James J. Park, Simon James Fong, Yi Pan, Yunsick Sung
發行者Springer Science and Business Media Deutschland GmbH
頁面387-394
頁數8
ISBN(列印)9789811593420
DOIs
出版狀態Published - 2021
事件11th International Conference on Computer Science and its Applications, CSA 2019 and 14th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2019 - Macao, China
持續時間: 2019 十二月 182019 十二月 20

出版系列

名字Lecture Notes in Electrical Engineering
715
ISSN(列印)1876-1100
ISSN(電子)1876-1119

Conference

Conference11th International Conference on Computer Science and its Applications, CSA 2019 and 14th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2019
國家/地區China
城市Macao
期間19-12-1819-12-20

All Science Journal Classification (ASJC) codes

  • 工業與製造工程

指紋

深入研究「Mobile Charger Planning for Wireless Rechargeable Sensor Network Based on Ant Colony Optimization」主題。共同形成了獨特的指紋。

引用此