迈向三维架构:细胞气体维度的比较研究

A. Morales-Reyes, Asmaa Al-Naqi, A. Erdogan, T. Arslan
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引用次数: 9

摘要

细胞遗传算法(cGAs)不仅能够解决复杂的优化问题,而且在效率和功效方面都优于集中式遗传算法(GAs)。本文提出的研究旨在分析和比较二维和三维蜂窝气体,同时保持其总体配置约束,如人口规模、邻里半径、局部选择方法、替换策略等。本文的主要目的是为三维自适应优化引擎架构的未来发展提供对增加细胞维度的优势的广泛见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards 3D Architectures: A Comparative Study on Cellular GAs Dimensionality
Cellular Genetic Algorithms (cGAs) have shown their ability to solve not only difficult optimization problems, but also outperform centralized Genetic Algorithms (GAs) in terms of efficiency and efficacy. The study herein presented aims to analyze and compare 2D and 3D cellular GAs, while maintaining in general their configuration constraints such as population size, neighbourhood radius, local selection method, replacement polices, among others. A primary objective of this paper is to provide a wide insight into the advantages of increasing cellular dimensionality for future development of 3D adaptive optimization engine architectures.
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