Artificial Bee Colony algorithm for Traveling Salesman Problem

Abstract

Travelling salesman problem (TSP) is a fundamental combinatorial optimization model studied in the operations research community for nearly half a century.It belongs to the class of NP-Complete problems.It has been proved that evolutionary algorithms are effective and efficient, with respect to the traditional methods for solving NP-Complete problems like TSP, with avoidance trapping in local minima areas.Artificial Bee Colony (ABC) is a new swarm-based optimization algorithm, which inspired by the foraging behavior of honey bees.This paper uses artificial bee colony algorithm to solve traveling salesman problems, gives the specific solutions of artificial bee colony algorithm for solving traveling salesman problem, and makes simulation experiment for the problem.The results show that the algorithm can efficiently and quickly find optimal or sub-optimal solutions.