{"id":1154,"date":"2026-01-25T19:27:37","date_gmt":"2026-01-25T19:27:37","guid":{"rendered":"https:\/\/www.cs.ubbcluj.ro\/~meco\/critical-node-detection-for-maximization-of-connected-components-an-extremal-optimization-approach-2021\/"},"modified":"2026-02-01T12:08:49","modified_gmt":"2026-02-01T12:08:49","slug":"critical-node-detection-for-maximization-of-connected-components-an-extremal-optimization-approach-2021","status":"publish","type":"post","link":"https:\/\/www.cs.ubbcluj.ro\/~meco\/critical-node-detection-for-maximization-of-connected-components-an-extremal-optimization-approach-2021\/","title":{"rendered":"Critical Node Detection for Maximization of Connected Components: An Extremal Optimization Approach (2021)"},"content":{"rendered":"<div class=\"entry-content\">\n<p>Soft Computing Models in Industrial and Environmental Applications<\/p>\n<h2>Authors<\/h2>\n<p>No\u00e9mi Gask\u00f3, Tam\u00e1s K\u00e9pes, M. Suciu, R. Lung<\/p>\n<h2>Abstract<\/h2>\n<p>Determining the critical nodes in a network given a certain network measure is a computational challenging problem that requires the design of adaptive and scalable algorithms. The number of connected components in a graph is an example of such a measure: in this case the nodes considered critical are those that, if removed from the network, maximize the number of connected components in the remaining graph. In this paper we approach this problem by using a new algorithm based on Extremal Optimization. Comparisons with existing algorithms conducted on synthetic and real world networks illustrate the potential of the proposed approach.<\/p>\n<h2>Citation<\/h2>\n<pre class=\"wp-block-preformatted\">@Inproceedings{Gask\u00f32021CriticalND,\n author = {No\u00e9mi Gask\u00f3 and Tam\u00e1s K\u00e9pes and M. Suciu and R. Lung},\n booktitle = {Soft Computing Models in Industrial and Environmental Applications},\n title = {Critical Node Detection for Maximization of Connected Components: An Extremal Optimization Approach},\n year = {2021}\n}<\/pre>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Determining the critical nodes in a network given a certain network measure is a computational challenging problem that requires the design of adaptive and scalable algorithms. The number of connected components in a graph is an example of such a measure: in this case the nodes considered critical are those that, if removed from the network, maximize the number of connected components in the remaining graph. In this paper we approach this problem by using a new algorithm based on Extremal Optimization. Comparisons with existing algorithms conducted on synthetic and real world networks illustrate the potential of the proposed approach.<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[8,18,20],"_links":{"self":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1154"}],"collection":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/comments?post=1154"}],"version-history":[{"count":1,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1154\/revisions"}],"predecessor-version":[{"id":1520,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/1154\/revisions\/1520"}],"wp:attachment":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/media?parent=1154"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/categories?post=1154"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/tags?post=1154"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}