{"title":"Metaheuristics for Wireless Network Optimisation","authors":"M. Morgan, V. Grout","doi":"10.1109/AICT.2007.28","DOIUrl":null,"url":null,"abstract":"This paper introduces two new algorithms for the minimum connected dominating set (MCDS) problem with constraints applicable to wireless network design, based on simulated annealing and tabu search principles. Each algorithm is tested on a selection of random graphs and shown to produce significantly smaller connected dominating sets when compared to a number of established methods. The simulated annealing algorithm is found to favour large, sparse graphs while the tabu search heuristic prefers smaller dense instances. In conclusion, we consider the adaptation of these algorithms to hybrid techniques and comment on the possible use of hyper-heuristics.","PeriodicalId":334924,"journal":{"name":"The Third Advanced International Conference on Telecommunications (AICT'07)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Third Advanced International Conference on Telecommunications (AICT'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICT.2007.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper introduces two new algorithms for the minimum connected dominating set (MCDS) problem with constraints applicable to wireless network design, based on simulated annealing and tabu search principles. Each algorithm is tested on a selection of random graphs and shown to produce significantly smaller connected dominating sets when compared to a number of established methods. The simulated annealing algorithm is found to favour large, sparse graphs while the tabu search heuristic prefers smaller dense instances. In conclusion, we consider the adaptation of these algorithms to hybrid techniques and comment on the possible use of hyper-heuristics.