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This paper presents a new genetic algorithm for the minimum vertex cover problem. It uses interval-valued fitness and greedy error correction to obtain phenotypes (candidate solutions). By the interval-valued fitness the fitness of the candidate solution is measured not only for the whole graph, but for some of its disjoint subgraphs. A new candidate solution is obtained from those subgraphs that have the best performance among the subgraphs of the candidates with the same set of vertices. Thedoi:10.12700/aph.18.4.2021.4.6 fatcat:3eab4ba43bhwnbclc66z4dbw5y