Logistic Regression for Parameter Tuning on an Evolutionary Algorithm
I.C.O. Ramos, Marco C. Goldbarg, Elizabeth Ferreira Gouvêa Goldbarg, Adrião Duarte Dória Neto · 2005
The investigation of the parameters for which algorithms have their best performance is crucial when working with metaheuristics. This paper proposes the utilization of logistic regression, a statistical tool, for parameter tuning of an evolutionary algorithm called ProtoG. To illustrate the ideas proposed in this work, the algorithm is applied to the traveling salesman problem.