|Títol||A Biased Random Key Genetic Algorithm for the Weighted Independent Domination Problem|
|Publication Type||Conference Paper|
|Year of Publication||2019|
|Authors||Corominas GRódriguez, Blum C, Blesa MJ|
|Conference Name||Student Workshop of the Genetic and Evolutionary Computation Conference (GECCO 2019)|
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.
- Quant a IIIA