Implementation of Aco Algorithm for Edge Detection and Sorting Salesman Problem

This paper presents an Ant Colony Optimization-based technique for image edge detection and solve TSP.The proposed method establishes a pheromone matrix that represents the edge information at each pixel based on the routes formed by ants dispatched on the image. The movement of the ants is guided by the local variation of the image’s intensity values.In TSP, a set of cities is given and distance between each of them is known. The goal is to find the shortest tour that allows each city to be visited once and only once. ACO is a population-based metaheuristic that mimics the foraging behaviour of ants to find approximate solutions to difficult optimization problems. In ACO, the problem is tackled by simulating a number of artificial ants moving on a graph that encodes the problem itself.