Abstract
To find the parameters’ configuration relationship of the Ant Colony Algorithm, based on the ecological actions about ants, the distributing multiformity of ant colony pheromone, the pheromone updating strategy and the mutant of information difference were applied to Microhabitat Ant Colony Optimization (MACO). The parameters, α0, β0, kα and kβ of MACO were configured by the orthogonal experiment to enhance the performance of the algorithm, in which the interactions of α0 and β0, kα and kβ, α0 and kα, β0 and kβwere also analyzed. Some benchmarks of TSP and JSSP were solved by MACO which showed significant optimize performance with configured parameters.
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