Multicriteria optimization based on neural network approximation of decision maker's utility function

被引：1
作者：
Karpenko A.P. [1 ]
Mukhlisullina D.T. [1 ]
Ovchinnikov V.A. [2 ]
机构：
[1] Bauman Moscow State Technical University, Moscow
[2] LLC Laduga, Moscow
来源：
Optical Memory and Neural Networks (Information Optics) | 2010年 / 19卷 / 03期
关键词：
approximation; combustion engine; direct adaptive method; multicriteria optimization; neural network;
D O I：
10.3103/S1060992X10030045
中图分类号：
学科分类号：
摘要：
A direct adaptive method of multicriteria optimization based on neural network approximation of a decision maker's utility function is introduced. Efficiency of method is analyzed via two- and three- criterion test problems solving. Efficiency testing results are shown. The method implementation as an optimization module for PRADIS (Program for Analysis of Dynamic Systems) is described. Practical application of the method for solving two-criterion optimization problem of combustion engine mechanical subsystem is carried out. © 2010 Allerton Press, Inc.
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页码：227 / 236
页数：9
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