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首页> 外文期刊>International Journal of Bio-Inspired Computation >Quantum inspired cuckoo search algorithm for graph colouring problem
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Quantum inspired cuckoo search algorithm for graph colouring problem

机译:用于图着色问题的量子启发式布谷鸟搜索算法

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摘要

The graph colouring problem (GCP) is one of the most interesting, studied and difficult combinatorial optimisation problems. That is why, several approaches were developed for solving this problem, including exact approaches, heuristic approaches, metaheuristics and hybrid approaches. In this paper, we try to solve the graph colouring problem using a new approach based on the quantum inspired cuckoo search algorithm. The first contribution consists in defining an appropriate quantum representation based on qubit representation to represent the graph colouring solutions. The second contribution is the proposition of a novel measure operator based on the adjacency matrix. The third contribution involves the proposition of an adapted hybrid quantum mutation operation. To show the feasibility and the effectiveness of the algorithm, we have used the standard DIMACS benchmark, and the obtained results are very encouraging.
机译:图形着色问题(GCP)是最有趣,研究最困难的组合优化问题之一。因此,开发了几种解决此问题的方法,包括精确方法,启发式方法,元启发式方法和混合方法。在本文中,我们尝试使用一种基于量子布谷鸟搜索算法的新方法来解决图形着色问题。第一个贡献在于基于量子位表示法定义合适的量子表示法来表示图形着色解决方案。第二个贡献是基于邻接矩阵的新型度量算子的命题。第三个贡献是提出了一个适合的混合量子突变操作的命题。为了显示该算法的可行性和有效性,我们使用了标准的DIMACS基准,获得的结果令人鼓舞。

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