对科学发展轮廓中元启发式未来的贡献

N. A. Sampaio, J. M. Reis, Maximilian Espuny, Ronald Paland Cardoso, F. M. Gomes, F. M. Pereira, Luís César Ferreira, Motta Barbosa, Gilberto Santos, Messias Borges Silva
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引用次数: 8

摘要

元启发式算法通过识别一组变量之间的最佳组合来解决优化问题,以增强函数。在元启发式中,这项工作的主要目的是展示与优化和元启发式相关的过程的研究问题的发展,重点是对那些具有更大发展可能性的问题的预测。优化过程是人工智能、优化、物流和其他应用中研究最多的领域之一。这项工作的主要贡献是确定了过程优化和元启发式主题中包含的主要问题;对上述主题的扩大和缩小的分析;对趋同与发散的理解;并分析了50篇最常被提及的文章中出现的发展阶段。主要发现是分析优化过程和元启发式研究课题的发展,重点是预测最有可能发展的课题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contributions to the future of metaheuristics in the contours of scientific development
Abstract Metaheuristic algorithms solve optimisation problems by identifying the best combination among a set of variables to enhance a function. Within metaheuristics, the main purpose of this work is that of showing the development of research issues about processes related to optimisation and metaheuristics, with a focus on the projection of those issues with greater possibility of development. Optimization processes is one of the most studied fields in artificial intelligence, optimization, logistics, and other applications The main contributions of this work were the identification of the main issues contained in the themes of process optimization and metaheuristics; an analysis of the expansion and retraction of the aforementioned theme; an understanding of convergence and divergence; and an analysis of the stages of development as presented in the gaps of the fifty most commonly mentioned articles. The main finding was to analyze the development of research topics on optimization processes and metaheuristics, focusing on projecting the topics most likely to develop.
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