基于人工智能的优化框架，用于优化特种微合金多相钢的成分和热机械加工工艺安排

IF 2.2 3区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

Engineering Optimization Pub Date : 2024-05-29 DOI:10.1080/0305215x.2024.2354313

M. Kafuko, S. Srinivasan

引用次数: 0

摘要

本文提出了一种基于人工智能的启发式方法，用于优化化学成分和热机械加工进度，以获得特殊的微合金多相钢。

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 artificial intelligence-based optimization framework for the optimal composition and thermomechanical processing schedule for specialized micro-alloyed multiphase steels

An artificial intelligence-based heuristic approach is presented to optimize the chemical composition and the thermomechanical processing schedule to obtain specialized micro-alloyed multiphase ste...

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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.