Implementing Discrete Cuckoo Search Algorithm for TSP using MPI and Beowulf Cluster
Bhavana V1, Varshini Ramesh2, Sivagami M3
1Bhavana V, Student, School of Computer Science Engineering, Vellore Institute of Technology, Chennai, India.
2Varshini Ramesh, Student,School of Computer Science Engineering, Vellore Institute of Technology, Chennai, India.
3Sivagami M, Associate Professor, School of Computer Science Engineering, Vellore Institute of Technology, Chennai, India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 554-560 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6711068819/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: The main aim of the proposed work is to find a better quality solution for Travelling Salesman Problem using Cuckoo Search Algorithm efficiently. Parallelizing is done to increase the quality of result. To implement parallelism across the nodes, MPI has been used. A Beowulf cluster was also created to achieve parallelism. The Discrete Cuckoo Search optimization code was run on a single system with multiple cores and on the Beowulf cluster. A thorough analysis has been performed to assess the efficacy of this optimization and the results are shown.
Keyword: Discrete Cuckoo Search Optimization Algorithm, MPI, Travelling Salesman Problem.
Scope of the Article: Discrete Optimization.