Optimization has been a hot topic due to its inevitably in the development of new algorithms in almost every applied branch of Mathematics. Despite the broadness of optimization techniques in research fields, there is always an open scope of further refinement. We present here an overview of nature-inspired optimization with a subtle background of fundamentals and classification and their reliability applications. An attempt has been made to exhibit the contrast nature of multi objective optimization as compared to single objective optimization. Though there are various techniques to achieve the optimality in optimization problems but nature inspired algorithms have proved to be very efficient and gained special attention in modern research problems. The purpose of this article is to furnish the foundation of few nature inspired optimization techniques and their reliability applications to an interested researcher. KeywordsMetaheuristics, Grey wolf optimizer, Multi-objective optimization, Reliability optimization

中文翻译：

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少数自然启发式优化技术及其可靠性应用概述

由于在数学的几乎每个应用分支中都不可避免地会开发新算法，因此优化一直是一个热门话题。尽管优化技术在研究领域中很广泛，但始终存在着进一步完善的开放范围。我们在此概述自然启发式的优化，并具有基本原理和分类及其可靠性应用的微妙背景。已经尝试展示与单目标优化相比的多目标优化的对比性质。尽管有多种技术可以实现优化问题的最优性，但是自然启发算法已被证明是非常有效的，并在现代研究问题中得到了特别的关注。本文的目的是为感兴趣的研究人员提供一些自然启发的优化技术及其可靠性应用的基础。关键字：元启发式，灰狼优化器，多目标优化，可靠性优化