A conceptual framework for combining artificial intelligence and optimization in engineering design

被引:26
作者
Cagan, J
Grossmann, IE
Hooker, J
机构
[1] Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA
[2] Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh
基金
美国安德鲁·梅隆基金会; 美国国家科学基金会;
关键词
artificial intelligence; design; operations research; optimization;
D O I
10.1007/BF01607055
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Research in artificial intelligence and optimization (OR) has had significant impact on the formulation and solution of computational methods in engineering design. This paper presents a conceptual framework for understanding a mole powerful technology that is evolving from a combination of these approaches. The paper first proposes generalized representations of engineering design models that involve quantitative and qualitative aspects. Second, it presents a general classification of AI and OR models in terms of model attributes, in order to establish mappings with generic solution techniques. Third, the requirements of solution methods are discussed, as well as several schemes for the integration of AI and optimization to identify future research directions. Several specific approaches are included to illustrate various ways in which AI and optimization can be combined for tackling computational design models.
引用
收藏
页码:20 / 34
页数:15
相关论文
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