旅行商问题的量子布谷鸟搜索算法

Sumit Laha
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引用次数: 8

摘要

量子算法和布谷鸟搜索算法作为一种新兴的进化技术,由于其在工程和管理的各种应用中更有效地探索搜索空间,从而具有全局和局部搜索的能力,近年来引起了人们的广泛关注。据我们所知,本文首先考虑应用量子启发的布谷鸟搜索算法来解决经典的旅行商问题。本文提出了一种求解旅行商问题的量子嵌入式布谷鸟搜索算法。在模拟退火算法中采用了基于邻域搜索的构造和随机启发式方法,以加快搜索过程,获得更好的解质量。本文用从TSP库中提取的几个基准测试问题实例对所提出的方法进行了测试。计算结果表明,所提出的混合方法与文献中最先进的方法相比具有很强的竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A quantum-inspired cuckoo search algorithm for the travelling salesman problem
The quantum algorithm and the cuckoos search algorithm as emerging novel evolutionary techniques has recently drawn a lot of research interest due to their capability to search globally as well as locally by exploring the search space more efficiently in various applications of engineering and management. To the best of our knowledge, this paper first considers the application of quantum-inspired cuckoo search algorithm to solve the classic travelling salesman problems. In this paper, we present a quantum embedded cuckoo search algorithm for the travelling salesman problem. To accelerate the search process for better solution quality, some neighborhood search based construction and stochastic heuristic approaches is utilized in the simulated annealing algorithm. The proposed method is tested with several benchmark test problem instances taken from the TSP library in the literature. The computational results demonstrate that the proposed hybrid method is very competitive with the state-of-the-art procedures in the literature.
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