Quantum-inspired evolutionary algorithms: a survey and empirical study
Quantum-inspired evolutionary algorithms: a survey and empirical study
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DOI：
10.1007/s10732-010-9136-0
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发表时间：
2011-06
影响因子：
2.7
通讯作者：
Gexiang Zhang
中科院分区：
文献类型：
--
作者：
Gexiang Zhang
量子进化算法是与量子计算和进化算法之间复杂相互作用相关的三个主要研究领域之一，正在重新受到关注。受量子启发的进化算法是一种针对经典计算机而不是量子机械硬件的新进化算法。本文提供了一个统一的框架，并对这个快速发展的领域的最新工作进行了全面的调查。在介绍了量子进化算法背后的主要概念之后，我们提出了与多种量子进化算法相关的关键思想，概述了它们之间的差异，调查了从组合优化到数值优化的理论发展和应用，并比较了这些不同方法的优点和局限性。最后，进行了一项小型比较研究，以评估不同类型的量子启发进化算法的性能，并就该领域一些最有前途的未来研究进展得出结论。
Quantum-inspired evolutionary algorithms, one of the three main research areas related to the complex interaction between quantum computing and evolutionary algorithms, are receiving renewed attention. A quantum-inspired evolutionary algorithm is a new evolutionary algorithmfor a classical computerrather than for quantum mechanical hardware. This paper provides a unified framework and a comprehensive survey of recent work in this rapidly growing field. After introducing of the main concepts behind quantum-inspired evolutionary algorithms, we present the key ideas related to the multitude of quantum-inspired evolutionary algorithms, sketch the differences between them, survey theoretical developments and applications that range from combinatorial optimizations to numerical optimizations, and compare the advantages and limitations of these various methods. Finally, a small comparative study is conducted to evaluate the performances of different types of quantum-inspired evolutionary algorithms and conclusions are drawn about some of the most promising future research developments in this area.