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

Fan Hsun Tseng, Hsin Hung Cho, Chin Feng Lai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationAdvances in Computer Science and Ubiquitous Computing - CSA-CUTE 2019
EditorsJames J. Park, Simon James Fong, Yi Pan, Yunsick Sung
PublisherSpringer Science and Business Media Deutschland GmbH
Pages387-394
Number of pages8
ISBN (Print)9789811593420
DOIs
Publication statusPublished - 2021
Event11th 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
Duration: 2019 Dec 182019 Dec 20

Publication series

NameLecture Notes in Electrical Engineering
Volume715
ISSN (Print)1876-1100
ISSN (Electronic)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
Country/TerritoryChina
CityMacao
Period19-12-1819-12-20

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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