Augmentation of Travelling Salesman Problem using Bee Colony Optimization
Anshul Singh1, Devesh Narayan2
1Anshul Singh, Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai, India.
2Mr. Devesh Narayan, Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai, India..
Manuscript received on July 01, 2012. | Revised Manuscript received on July 05, 2012. | Manuscript published on July 10, 2012. | PP: 61-65 | Volume-1, Issue-2, July 2012. | Retrieval Number: B0152061212/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Animals with social behaviors often uncover optimal solutions to a range of problems when compared to other techniques. This advantage is extensively used nowadays for a variety of applications. The bee colony optimization (BCO) is inspired by bees foraging behavior that includes colonies of artificial bees capable of solving combinatorial optimization problems e.g. Travelling Salesman Problem. K-opt local search for the value of k as 3 repeatedly reconnects random three edges of the graph after disconnecting so as to obtain refined path. In this article BCO and k-opt local search, the two heuristic techniques for optimization, are combined together to acquire sophisticated results. Comparisons of the proposed method with nearest neighborhood approach is performed and shown with presented system proved to be superior to the rest.
Keywords: Bee Colony optimization, k-opt local search, waggle dance, Travelling Salesman Problem.