Genetic Algorithms : Comparing Evolution With and Without a Simulated Annealing-inspired Selection

Abstract: The Genetic Algorithm (GA) is an interesting problem solving algorithm which takes inspiration from evolution in order to self-improve and reach good solutions to problems by reproduction and mutation. This thesis compares a GA with and without a Simulated Annealing (SA) inspired selection when it comes to solving three different instances of the Traveling Salesman Problem (TSP). SA was found to be able to help the GA reach better solutions, but the results also depended on other parameters within the GA itself.