Mapping the convergence of genetic algorithms

This paper examines the convergence of genetic algorithms using a cluster-analytic-type procedure. The procedure is illustrated with a hybrid genetic algorithm applied to the quadratic assignment problem. Results provide valuable insight into how population members are selected as the number of generations increases and how genetic algorithms approach stagnation after many generations.