{"title":"一种提高复杂网络鲁棒性的遗传算法","authors":"C. Pizzuti, Annalisa Socievole","doi":"10.1109/ICTAI.2018.00085","DOIUrl":null,"url":null,"abstract":"A method to enhance the robustness of a network, based on Genetic Algorithms, is proposed. The approach optimizes the effective graph resistance of a network, a measure of robustness derived from the field of electric circuit analysis, that can be computed as a cumulative sum of the eigenvalues of the Laplacian matrix associated with the network. Specialized variation operators allow the method to find a solution almost always coinciding with that obtained by the exhaustive search. Experiments on synthetic and real life networks show that the approach outperforms heuristic strategies extensively investigated, by giving the exact solution in a high percentage of the considered networks.","PeriodicalId":254686,"journal":{"name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"128 7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Genetic Algorithm for Improving Robustness of Complex Networks\",\"authors\":\"C. Pizzuti, Annalisa Socievole\",\"doi\":\"10.1109/ICTAI.2018.00085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method to enhance the robustness of a network, based on Genetic Algorithms, is proposed. The approach optimizes the effective graph resistance of a network, a measure of robustness derived from the field of electric circuit analysis, that can be computed as a cumulative sum of the eigenvalues of the Laplacian matrix associated with the network. Specialized variation operators allow the method to find a solution almost always coinciding with that obtained by the exhaustive search. Experiments on synthetic and real life networks show that the approach outperforms heuristic strategies extensively investigated, by giving the exact solution in a high percentage of the considered networks.\",\"PeriodicalId\":254686,\"journal\":{\"name\":\"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)\",\"volume\":\"128 7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTAI.2018.00085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAI.2018.00085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Genetic Algorithm for Improving Robustness of Complex Networks
A method to enhance the robustness of a network, based on Genetic Algorithms, is proposed. The approach optimizes the effective graph resistance of a network, a measure of robustness derived from the field of electric circuit analysis, that can be computed as a cumulative sum of the eigenvalues of the Laplacian matrix associated with the network. Specialized variation operators allow the method to find a solution almost always coinciding with that obtained by the exhaustive search. Experiments on synthetic and real life networks show that the approach outperforms heuristic strategies extensively investigated, by giving the exact solution in a high percentage of the considered networks.