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Memetic algorithms and memetic computing optimization: A literature review

机译：模因算法和模因计算优化：文献综述

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摘要

Memetic computing is a subject in computer science which considers complex structures such as the combination of simple agents and memes, whose evolutionary interactions lead to intelligent complexes capable of problem-solving. The founding cornerstone of this subject has been the concept of memetic algorithms, that is a class of optimization algorithms whose structure is characterized by an evolutionary framework and a list of local search components. This article presents a broad literature review on this subject focused on optimization problems. Several classes of optimization problems, such as discrete, continuous, constrained, multi-objective and characterized by uncertainties, are addressed by indicating the memetic "recipes" proposed in the literature. In addition, this article focuses on implementation aspects and especially the coordination of memes which is the most important and characterizing aspect of a memetic structure. Finally, some considerations about future trends in the subject are given.
机译：模因计算是计算机科学中的一门学科，它考虑了诸如简单代理和模因的组合之类的复杂结构，其进化相互作用导致了能够解决问题的智能复合体。该主题的基础是模因算法的概念，这是一类优化算法，其结构以进化框架和一系列本地搜索组件为特征。本文针对此问题提供了广泛的文献综述，重点是优化问题。通过指出文献中提出的模因“配方”，可以解决几类优化问题，例如离散，连续，约束，多目标和具有不确定性的特征。此外，本文重点关注实现方面，尤其是模因的协调，这是模因结构最重要的特征。最后，给出了关于该学科未来趋势的一些考虑。

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