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Hybrid Genetic Algorithm: Traveling Salesman Problem

  • Sunita SinghalEmail author
  • Hemlata Goyal
  • Parth Singhal
  • Jyoti Grover
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 3)

Abstract

A genetic algorithm has three main operators namely selection, crossover and mutation. Each operator has various sub operators. Selection of sub operator that can be applied on particular problem is difficult task. Thus this paper proposes a hybrid genetic algorithm (HGA). HGA algorithm finds the sub operators that can be applied on traveling salesman problem. After that it finds the threshold value. Based on threshold value it switches from one sub operator to other sub operator. The HGA algorithm score over existing genetic algorithm on traveling salesman problem on large number of cities.

Keywords

Hybrid genetic algorithms Traveling salesman problem Genetic algorithms Combinational optimization 

Notes

Acknowledgments

The author gratefully thankful to Rishab Rakshit student of SMIT who did simulation in summer project’16 at MUJ.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Sunita Singhal
    • 1
    Email author
  • Hemlata Goyal
    • 1
  • Parth Singhal
    • 1
  • Jyoti Grover
    • 1
  1. 1.School of Computing and Information TechnologyManipal University JaipurJaipurIndia

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