A Fast Bee Colony Algorithm to Solve NP-Hard Problems
The Bee Colony Optimization (BCO), is one the nature inspired algorithms used to solve very complex NP-hard problems very effectively and efficiently. This paper presents an algorithm based on bee colony optimization to solve a combinatorial optimization problem called Random Traveling Salesman Problem (RTSP). We present an algorithm which finds a shortest tour for a traveling salesman with a reduced amount of time required to complete the tour. The results obtained for the randomly generated instances of TSP are then compared with the results obtained with the other very well known combinatorial optimization algorithms. The proposed algorithm produces very good quality solutions in acceptable time in compare to other algorithms.
Keywords: Meta heuristics, bee colony optimization, combinatorial optimization, swarm intelligence, random traveling salesman problem.