TitleA Biased Random Key Genetic Algorithm for the Weighted Independent Domination Problem
Publication TypeConference Paper
Year of Publication2019
AuthorsCorominas GRódriguez, Blum C, Blesa MJ
Conference NameStudent Workshop of the Genetic and Evolutionary Computation Conference (GECCO 2019)
PublisherACM Press
Abstract

This work deals with an NP-hard problem in graphs known as the weighted independent domination problem. We propose a biased random key genetic algorithm for solving this problem. The most important part of the proposed algorithm is a decoder that translates any vector of real-values into valid solutions to the tackled problem. The experimental results, in comparison to a state-of-the-art population-based iterated greedy algorithm from the literature, show that our proposed approach has advantages over the state-of-the-art algorithm in the context of the more dense graphs in which edges have higher weights than vertices.