过去五年混合式头脑风暴优化算法的策略与应用:综述

Pub Date : 2024-06-03 DOI:10.1093/jigpal/jzae051
Dragan Simić, Z. Bankovic, José R. Villar, J. Calvo-Rolle, V. Ilin, S. Simic, Svetlana Simić
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引用次数: 0

摘要

一般来说,优化被认为是为给定问题的变量寻找最优值,以最小化或最大化一个或多个目标函数的过程。头脑风暴优化(BSO)算法通过模仿人类产生想法的过程来解决复杂的优化问题,在这个过程中,一群人共同解决一个问题。本文旨在介绍过去 5 年中的混合 BSO 算法解决方案。这项研究可分为两个部分:策略和应用。第一部分展示了混合 BSO 算法的不同策略,旨在提高原始 BSO 算法的各种能力。第二部分介绍了过去五年中在优化、预测和特征选择过程中的实际应用。
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Past five years on strategies and applications in hybrid brain storm optimization algorithms: a review
Optimization, in general, is regarded as the process of finding optimal values for the variables of a given problem in order to minimize or maximize one or more objective function(s). Brain storm optimization (BSO) algorithm solves a complex optimization problem by mimicking the human idea generating process, in which a group of people solves a problem together. The aim of this paper is to present hybrid BSO algorithm solutions in the past 5 years. This study could be divided into two parts: strategies and applications. In the first part, different strategies for the hybrid BSO algorithms intended to improve the various ability of the original BSO algorithm are displayed. In the second part, the real-world applications in the past five years in optimization, prediction and feature selection processes are presented.
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