A Genetic Method using Hybrid Crossover for Solving Travelling Salesman Problem
Anubhav Kumar Prasad1, Dharm Raj Singh2, Pankaj3 

1Anubhav Kumar Prasad, Research Scholar, Department of Science and Technology- Centre for Interdisciplinary Mathematical Sciences, Institute of Science Banaras Hindu University, Varanasi, Uttar Pradesh, India, 221005.
2Dr. Dharm Raj Singh, Assistant Professor and Head of Department of, Computer Application, Jagatpur Degree College, Varanasi, Uttar Pradesh, India, 221005.
3Dr. Pankaj, Assistant Professor, Mathematics Section, Mahila Maha Vidyalaya, Banaras Hindu University, Varanasi, Uttar Pradesh, India ,221005.

Manuscript received on 17 March 2019 | Revised Manuscript received on 23 March 2019 | Manuscript published on 30 July 2019 | PP: 5066-5072 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1897078219/19©BEIESP | DOI: 10.35940/ijrte.B1897.078219
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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: This paper proposes a Genetic approach using Hybrid Crossover for Solving the Travelling Salesman Problem. Proposed hybrid method generates an initial population using Nearest Neighbor (NN) approach which is modified using “Sub-Path Mutation” (SPM) process. Modified population undergoes Distance Preserving Crossover (DPX) [2] and 2-opt Optimal mutation (2-opt) [1] to check for possible refinement. SPM searches position for the minimum distant city within a given path. This work is motivated by the algorithm developed by [3] who performed DPX and 2-opt mutation on the initial population generated using NN. For performance comparison, standard TSPLIB data is taken. The proposed hybrid method performances better in terms of % best error. It performs better than methods reported in [3 – 11].
Index Terms: Nearest Neighbor Approach, Distance Preserving Crossover, Sub-Path Mutation, 2-opt Mutation.

Scope of the Article: Problem Solving and Planning