Designing Pheromone Update Strategies with Strongly Typed Genetic Programming
نویسندگان
چکیده
Ant Colony algorithms are population-based methods widely used in combinatorial optimization problems. We propose a strongly typed genetic programming approach to automatically evolve the communication mechanism that allows ants to cooperatively solve a given problem. Results obtained with several TSP instances show that the evolved pheromone update strategies are effective, exhibit a good generalization capability and are competitive with human designed variants.
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