On the Faster Ant Colony Optimization Algorithm

The pheromone trails in ACO are used to reflect the ants´ search experience, so the quality of the pheromone is crucial to the success of ACO. The main factors affecting the quality of the pheromone include the strategy of updating the pheromone and the quality of the constructed solutions. In order to improve the constructed solutions, this paper presents a method to analyze the invalid components of the constructed solution, and then repair the invalid components with immunity operator. When the pheromone density on the components are updated according the improved solution, they will more exactly reflect the character of high quality solution, so it will speed the positive feedback procedure. We examine the algorithm with examples of TSP and gain promising result.