A deterministic global design optimization method for nonconvex generalized polynomial problems

被引：5
|
作者：
Lo, CS
Papalambros, PY
机构：
[1] Design Laboratory, Department of Mechanical Engineering and Applied Mechanics, The University of Michigan, Ann Arbor, MI
[2] Vehicle Systems Synthesis and Analysis, Midsize Car Division, General Motors Corp, Warren, MI
来源：
JOURNAL OF MECHANICAL DESIGN | 1996年 / 118卷 / 01期
关键词：
D O I：
10.1115/1.2826859
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
A new design optimization method is described for finding global solutions of models with a nonconvex objective function and nonlinear constraints. All functions are assumed to be generalized polynomials. By introducing new variables, the original model is transformed into one with a linear objective function, one convex and one reversed convex constraint. A two-phase algorithm that includes global feasible search and focal optimal search is used for globally optimizing the transformed model. Several examples illustrate the method.
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页码：75 / 81
页数：7
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