JOURNAL ARTICLE

A new quantum-inspired genetic algorithm for solving the travelling salesman problem

Abstract

This paper presents a new algorithm for solving the travelling salesman problem (TSP). The TSP is one of the most known combinatorial optimisation problems. It is about finding the shortest Hamiltonian cycle relating N cities. The algorithm is inspired from both genetic algorithms and quantum computing fields. It extends the standard genetic algorithms by combining them to some concepts and principles provided from quantum computing field such as quantum bit, states superposition and interference. The obtained results from the application of the proposed algorithm on some instances of TSP are significantly better than those provided by standard genetic algorithms.

Keywords:
Travelling salesman problem Quantum computer Algorithm Computer science Genetic algorithm 2-opt Hamiltonian path Lin–Kernighan heuristic Superposition principle Quantum Quantum algorithm Hamiltonian (control theory) Field (mathematics) Mathematical optimization Mathematics Theoretical computer science Graph Physics

Metrics

87
Cited By
4.60
FWCI (Field Weighted Citation Impact)
6
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Quantum Computing Algorithms and Architecture
Physical Sciences →  Computer Science →  Artificial Intelligence
Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
DNA and Biological Computing
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology

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