A Modified-ABC: An Explicit-Memory Based Approach with a New Memory Updating and Retrieval in Dynamic Environments

M. Shakeri, M. Dadvar
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引用次数: 1

Abstract

The Artificial Bee Colony (ABC) algorithm is considered as one of the swarm intelligence optimization algorithms. It has been extensively used for the applications of static type. Many practical and real-world applications, nevertheless, are of dynamic type. Thus, it is needed to employ some optimization algorithms that could solve this group of the problems that are of dynamic type. Dynamic optimization problems in which change(s) may occur through the time are tougher to face than static optimization problems. In this paper, an approach based on the ABC algorithm enriched with explicit memory and population clustering scheme, for solving dynamic optimization problems is proposed.
改进的abc:一种基于显式记忆的动态环境下新的记忆更新和检索方法
人工蜂群(Artificial Bee Colony, ABC)算法被认为是群体智能优化算法的一种。它已广泛用于静态类型的应用。然而,许多实际和现实世界的应用程序是动态类型的。因此,需要采用一些优化算法来解决这组动态类型的问题。随着时间的推移,动态优化问题可能会发生变化,这比静态优化问题更难面对。本文提出了一种基于ABC算法的求解动态优化问题的方法。
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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