Solving Nonconvex Optimization Problems in Systems and Control: A Polynomial B-spline Approach

被引：2
|
作者：
Gawali, Deepak [1 ,3 ]
Zidna, Ahmed [2 ]
Nataraj, Paluri S. V. [3 ]
机构：
[1] Vidyavardhinis Coll Engn & Technol, Vasai, Maharashtra, India
[2] Univ Lorraine, Theoret & Appl Comp Sci Lab, Nancy, France
[3] Indian Inst Technol, Syst & Control Engn, Bombay, Maharashtra, India
来源：
MODELLING, COMPUTATION AND OPTIMIZATION IN INFORMATION SYSTEMS AND MANAGEMENT SCIENCES - MCO 2015, PT 1 | 2015年 / 359卷
关键词：
Polynomial B-spline; Global optimization; Polynomial optimization; Constrained optimization; GLOBAL OPTIMIZATION; RANGE;
D O I：
10.1007/978-3-319-18161-5_40
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Many problems in systems and control engineering can be formulated as constrained optimization problems with multivariate polynomial objective functions. We propose algorithms based on polynomial B-spline form for constrained global optimization of multivariate polynomial functions. The proposed algorithms are based on a branch-and-bound framework. We tested the proposed basic constrained global optimization algorithms by considering three test problems from systems and control. The obtained results agree with those reported in literature.
引用
收藏
页码：467 / 478
页数：12
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