A Memetic Approach to the Solution of Constrained Min-Max Problems

被引:0
作者
Filippi, Gianluca [1 ]
Vasile, Massimiliano [1 ]
机构
[1] Univ Strathclyde, Mech & Aerosp Engn, Glasgow, Lanark, Scotland
来源
2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2019年
基金
欧盟地平线“2020”;
关键词
worst case scenario; min-max; epistemic uncertainty; benchmark; OPTIMIZATION; ALGORITHM;
D O I
10.1109/cec.2019.8790124
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a novel memetic algorithm for the solution of constrained min-max problems that derive from the optimal design of complex systems under worst-case conditions. In this context the maximisation of a quantity of interest over the space of uncertain variables is required to identify the worst-case scenario (or worst-case solution under uncertainty). An optimal design vector is then identified such that the worst-case value of the quantity of interest is minimised. In the most general case, both maximisation and minimisation are subject to strict feasibility constraints. The ultimate goal of the minimisation problem is to identify the design solution that is feasible for all possible values of the uncertain parameters.
引用
收藏
页码:506 / 513
页数:8
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