Martins, PedroLadrón de Guevara, AntonioRamalhinho-Lourenço, Helena2020-05-042020-05-042014Martins P, Ladrón A, Ramalhinho H. Maximum cut-clique problem: ILS heuristics and a data analysis application. Int Trans Oper Res. 2014 Sep 5;22(5):775-809. DOI: 10.1111/itor.121200969-6016http://hdl.handle.net/10230/44396This paper focuses on iterated local search heuristics for the maximum cut‐clique (MCC, or clique neighborhood) problem. Given an undirected graph G = (V,E) and a clique C of G, the cut‐clique is the set of edges running between C and V\C, establishing the cut (C,V\C). The MCC in G is to find a clique with the largest number of edges in the neighborhood of the clique, also known as the maximum edge‐neighborhood clique. This problem has been recently introduced in the literature together with a number of applications, namely, in cell biology instances. However, it has only been addressed so far by exact methods. In this paper, we introduce the first approximate algorithms for tackling the MCC problem, compare the results with the exact methodologies, and explore a new application within marketing analysis, which provide a new alternative perspective for mining market basket problems.application/pdfengThis is the peer reviewed version of the following article: Martins P, Ladrón A, Ramalhinho H. Maximum cut-clique problem: ILS heuristics and a data analysis application. Int Trans Oper Res. 2014 Sep 5;22(5):775-809, which has been published in final form at http://dx.doi.org/10.1111/itor.12120. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1111/itor.12120Cut-cliquesClique’s edge neighborhoodIterated local search heuristicsDiscretized formulationsMarket basket analysisData mininginfo:eu-repo/semantics/openAccess