Ant Colony Optimization using Travelling Salesman Problem

The ant colony algorithm is a effective method to solve the problem of optimizing shortest path, which is one of the key technologies for navigation and path planning. There is a need for fast traversal algorithms, specifically to find a path from a source to destination with minimum cost. Cost can be distance, time, money, energy, etc. Travelling salesman problem (TSP) is used for combinational optimal problem. TSP is the most intensively studied problem in the area of optimization. Ant colony optimization (ACO) is based on the population metaheuristic method that can be used to find approximate solutions to difficult optimization problems. There have been many efforts in the past to provide time efficient solutions for the problem, both exact and approximate.Traveling salesman problem (TSP) belongs to hard problems. Since solving these problems need a lot of time for execution. This paper presents an attempt to decrees execution time using parallelization on multicore processor. To demonstrates the implementation of TSP using ant colony optimization(ACO) and show the comparision between serial and parallel execution, parallelization tool OPENMP was used. Keywords - Ant colony optimization, Travelling salesman Problem, pheromone update, parallel processing.