针对高维优化问题的粒子群优化与降维克里金代用模型相结合的改进优化方法

IF 2.2 3区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

Engineering Optimization Pub Date : 2024-02-12 DOI:10.1080/0305215x.2024.2309514

Junxiang Li, Ben Han, Jianqiao Chen, Zijun Wu

引用次数: 0

摘要

本文提出了一种将粒子群优化（PSO）算法与降维克里金代用模型（DK）相结合的改进优化方法，即 PSO + DK。在该方法中...

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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An improved optimization method combining particle swarm optimization and dimension reduction kriging surrogate model for high-dimensional optimization problems

An improved optimization method is proposed which combines the particle swarm optimization (PSO) algorithm with the dimension reduction kriging surrogate model (DK), namely PSO + DK. In this method...

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来源期刊

Engineering Optimization 管理科学-工程：综合

CiteScore

5.90

自引率

7.40%

发文量

审稿时长

3.5 months

期刊介绍： Engineering Optimization is an interdisciplinary engineering journal which serves the large technical community concerned with quantitative computational methods of optimization, and their application to engineering planning, design, manufacture and operational processes. The policy of the journal treats optimization as any formalized numerical process for improvement. Algorithms for numerical optimization are therefore mainstream for the journal, but equally welcome are papers which use the methods of operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, artificial intelligence, information theory and processing, and all methods which can be used in the quantitative modelling of the decision-making process. Innovation in optimization is an essential attribute of all papers but engineering applicability is equally vital. Engineering Optimization aims to cover all disciplines within the engineering community though its main focus is in the areas of environmental, civil, mechanical, aerospace and manufacturing engineering. Papers on both research aspects and practical industrial implementations are welcomed.