Adaptive Parallel Ant Colony Algorithm
An adaptive parallel ant colony algorithm is presented by considering the critical factors influencing the parallelization of the ant colony algorithm.Two different strategies for information exchange between processors are proposed: selecting the partner processor based on the fitness and on the distance.These strategies enable each processor to choose the partner processor to communicate and update the pheromone adaptively.In order to increase the ability of optimization and to avoid early convergence,we also propose a method of adjusting the iteration interval adaptively according to the diversity of the solutions. These techniques are tested on the traveling salesman problem using the massive parallel processors(MPP) Shengteng1800.Experimental results show that our algorithm can converge very quickly and has high speedup.