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

H. Talbi, A. Draa, M. Batouche
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引用次数: 91

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.
求解旅行商问题的一种新的量子启发遗传算法
提出了一种求解旅行推销员问题的新算法。TSP是最著名的组合优化问题之一。它是关于找到N个城市之间最短的哈密顿循环。该算法的灵感来自遗传算法和量子计算领域。将标准遗传算法与量子计算领域提供的量子比特、态叠加、干涉等概念和原理相结合,对标准遗传算法进行了扩展。该算法在一些TSP实例上的应用结果明显优于标准遗传算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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