PERBANDINGAN ALGORITME ANT COLONY OPTIMIZATION DENGAN ALGORITME GREEDY DALAM TRAVELING SALESMAN PROBLEM - Djamarus, Djasli; Mediawan, Meiril (TEKNOINFO, 2008)
Traveling Salesman Problem (TSP) is a classic NP (Non deterministic Polynomial) problem where a person has to make a tour to all known places exactly once, with a minimum cost. If there are N places to visit, there will be a number of (N-l)! routes to explore.Knowing the distance among all places, of course the shortest route can be determined. However, if there are so many places to visit, the number of route will increase very fast as the factorial function (much higher function compare to polynomial), of which the exploration to all routes in a deterministic approach will take a very long time.This limitation invites researchers to develop a new type of algorithm known as stochastic approach. Although there is no guarantee the best solution will be found, this type of algorithm propose an approximately solution in a much shorter time.In this work the Ant Colony Optimization (ACO), one of the stochastic algorithms, is apply to the TSP, the result is compare to the greedy algorithm in solving the same problem.Â