图表颜色问题的库库量子进化算法 (A Cuckoo Quantum Evolutionary Algorithm for the Graph Coloring Problem)

Based on the framework of the quantum-inspired evolutionary algorithm, a cuckoo quantum evolutionary algorithm (CQEA) is proposed for solving the graph coloring problem (GCP). To reduce iterations for the search of the chromatic number, the initial quantum population is generated by random initialization assisted by inheritance. Moreover, improvement of global exploration is achieved by incorporating the cuckoo search strategy, and a local search operation, as well as a perturbance strategy, is developed to enhance its performance on GCPs. Numerical results demonstrate that CQEA operates with strong exploration and exploitation abilities, and is competitive to the compared state-of-the-art heuristic algorithms.

翻译：根据量子驱动进化算法框架,为解决图表色化问题建议了一种酷酷量子进化算法(CQEA),为减少寻找染色数的迭代,最初的量子群是由随机初始化产生的,而继承则是由随机初始化产生的。此外,通过采用库库搜索策略,改进了全球探索,并制定了地方搜索行动以及近郊战略,以提高其在GCP的绩效。数字结果表明,CQEA的运作具有很强的勘探和开发能力,并且与比较的超高标准算法相比具有竞争力。