The Maximum Edge Weight Clique Problem: Formulations and Solution Approaches

Seyedmohammadhossein Hosseinian (), Dalila B. M. M. Fontes (), Sergiy Butenko (), Marco Buongiorno Nardelli (), Marco Fornari () and Stefano Curtarolo ()
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Seyedmohammadhossein Hosseinian: Texas A&M University
Dalila B. M. M. Fontes: Faculdade de Economia da Universidade do Porto, and LIAAD/INESC TEC, Rua Dr. Roberto Frias
Sergiy Butenko: Texas A&M University
Marco Buongiorno Nardelli: University of North Texas
Marco Fornari: Central Michigan University
Stefano Curtarolo: Duke University

A chapter in Optimization Methods and Applications, 2017, pp 217-237 from Springer

Abstract: Abstract Given an edge-weighted graph, the maximum edge weight clique (MEWC) problem is to find a clique that maximizes the sum of edge weights within the corresponding complete subgraph. This problem generalizes the classical maximum clique problem and finds many real-world applications in molecular biology, broadband network design, pattern recognition and robotics, information retrieval, marketing, and bioinformatics among other areas. The main goal of this chapter is to provide an up-to-date review of mathematical optimization formulations and solution approaches for the MEWC problem. Information on standard benchmark instances and state-of-the-art computational results is also included.

Keywords: Maximum Edge Weight Clique (MEWC); Standard Benchmark Instances; Broadband Network Design; Mathematical Optimization Formulations; Greedy Randomized Adaptive Search Procedure (GRASP) (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-68640-0_10

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