This paper deals with the study of population diversity in Genetic Algorithms for Job Shop Scheduling Problems. A definition of population diversity at the phenotype level and a way to compute it are given. Two diversity oriented selection procedures for GA are proposed. Their performances in terms of diversity and solution quality are tested against a standard Genetic Algorithm. Relations between population diversity and algorithm accuracy are shown through numerical experiments.
Carlos A. Brizuela, Nobuo Sannomiya