Ant Colony Optimization Lab Report

ANT COLONY OPTIMIZATION

Introduction

Ant Colony Optimization (ACO) is a metaheuristic approach which uses the technique to find the shortest path for a given problem. Dorigo, Maniezzo and Colorni were the first ones who proposed ACO algorithm called Ant System. Ant Colony Optimization algorithms are used to solve large number of hard combinatorial optimization problems such as traveling salesman problem, routing, quadratic assignment problem and in telecommunication networks. Whenever we are solving optimization problems, often the approach is to find all the possible solution and choose a best solution out of it. But some problems have such a large solution that it is impossible to arrive at an accurate solution in a reasonable time. These

Ant Colony optimization or Ant System is based on the natural foraging system found in the ant colony. Taking an example from real life scenario, we all know how ants make their way from their anthill to a food that might be found lying somewhere in and around the house. Biologists say that ants leave a chemical trail called pheromone which can be detected by other ants easily. The ants go in search of the food and the trail left behind by one ant will help the other ants to follow the same path to the food source. After a while, we can observe that there is line of ants from the anthill till the destination (food source). We may have also tried to distract the ant line in our childhood days but the ants will come back to the formation in no time. Even if the food source is removed, the ants tend to find other food sources and quickly one more line is formed to the second food source and the process continues. Ant Colony optimization was an original work of Dorigo, et al. when compared to other algorithms similar to this ACP works much better on the problem of finding shortest path to the city until 100

It is a NP-hard problem in combinatorial optimization. The first ACO algorithm which was called as ‘Ant System’ was first tested on Travelling Salesman problem. There may be situations wherein optimal solution is required for n number of problems in a short duration of time, the application of TSP helps in providing a solution for this. It is an important NP-hard optimization problem that arises in several managerial decision making in a