A Comprehensive Review of Metaheuristic Algorithms Inspired by Quantum Mechanics

S. S. Biswal, D. Swain, P. Rout, Adyashree Das, Ajay K. Mishra
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Abstract

This article comprehensively reviews the recently developed quantum mechanics-based optimization techniques. The quantum theory has been employed to speed up the evolutionary method and enhance the possibility of finding the optimal solution of conventional optimization techniques. Current developments in quantum computing have demonstrated that quantum theory can offer significant benefits over conventional theory for certain optimization techniques. The future prospective and benefits and drawbacks of this fresh category of quantum optimization techniques have been presented in this review. It also enables new researchers and algorithm developers to use these simple but extremely effective algorithms for problem-solving. This paper aims to give readers an overview of the fundamental elements and recent advances in optimization techniques so that they can develop and implement these for various applications. Finally, a few findings are reached, and future study on quantum-based optimization techniques is discussed.
受量子力学启发的元启发式算法综述
本文综述了近年来基于量子力学的优化技术。利用量子理论加快了进化方法的速度,提高了传统优化技术找到最优解的可能性。量子计算的最新发展表明,在某些优化技术上,量子理论可以提供比传统理论显著的优势。本文综述了这种新型量子优化技术的发展前景和优缺点。它还使新的研究人员和算法开发人员能够使用这些简单但非常有效的算法来解决问题。本文旨在为读者提供优化技术的基本要素和最新进展的概述,以便他们能够为各种应用开发和实现这些技术。最后,总结了一些研究成果,并对量子优化技术的未来研究进行了展望。
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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