Study of novel heterogeneous ant colony optimization algorithm for global path planning

Abstract

This paper presents a novel ACO algorithm to solve the global path planning problem, called Heterogeneous ACO (HACO) algorithm. We proposed HACO algorithm to improve the performance of ACO for global path planning in the previous paper. The HACO algorithm differs from the Conventional ACO (CACO) algorithm for the path planning in three respects. First, we proposed modified Transition Probability Function (TPF) and Pheromone Update Rule (PUR). Second, we newly introduced the Path Crossover (PC) in the PUR. Finally, we also proposed the first introduction of the heterogeneous ants in the ACO algorithm. We apply the proposed HACO algorithm to general path planning problem and we verify the effect of the each scheme through the simulation.