Evolving Ant Colony Optimization
. Ant Colony Optimization (ACO) is a promising new approach to combinatorial optimization. Here ACO is applied to the traveling salesman problem (TSP). Using a genetic algorithm (GA) to nd the best set of parameters, we demonstrate the good performance of ACO in nding good solutions to the TSP. KEYWORDS : Combinatorial Optimization; Traveling Salesman Problem; Heuristics; Ant Colony Optimization; Genetic Algorithm. 1. Introduction Social insects|ants, bees, termites and wasps|exhibit a collective problemsolving ability (Deneubourg and Goss, 1989; Bonabeau et al., 1997). In particular, several ant species are capable of selecting the shortest pathway, among a set of alternative pathways, from their nest to a food source (Beckers et al., 1990). Ants deploy a chemical trail (or pheromone trail) as they walk; this trail attracts other ants to take the path that has the most pheromone. This reinforcement process results in the selection of the shortest path: the rst ants coming back to...