元进化与广义进化行走算法综述
Review of Metaheuristics and Generalized Evolutionary Walk Algorithm
摘要：
元启发式算法通常是自然启发的，并且它们在解决全局最优化问题方面变得非常强大。在过去的三十年中，已经发展了十几种主要的元启发式算法，并且存在更多的元启发式算法的变体和混合。本文旨在提供一个自然启发式算法的概述，从一个简短的历史，他们的应用。我们试图分析这些算法的主要组成部分，以及它们如何以及为什么工作。然后，我们打算提供一个统一的观点，提出了一个广义的进化行走算法（GEWA）的元进化。最后，我们讨论一些重要的开放问题。
英文摘要：
Metaheuristic algorithms are often nature-inspired, and they are becoming very powerful in solving global optimization problems. More than a dozen of major metaheuristic algorithms have been developed over the last three decades, and there exist even more variants and hybrid of metaheuristics. This paper intends to provide an overview of nature-inspired metaheuristic algorithms, from a brief history to their applications. We try to analyze the main components of these algorithms and how and why they works. Then, we intend to provide a unified view of metaheuristics by proposing a generalized evolutionary walk algorithm (GEWA). Finally, we discuss some of the important open questions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
