Interior-Point Polynomial Algorithms in Convex Programming (Y. Nesterov and A. Nemirovskii)

SIAM Review ◽  
1994 ◽  
Vol 36 (4) ◽  
pp. 682-683 ◽  
Author(s):  
Yinyu Ye
Keyword(s):  
Convex Programming ◽  
Interior Point ◽  
Polynomial Algorithms

Proximal interior point approach in convex programming (ill-posed problems)*†

Optimization ◽  
1999 ◽  
Vol 45 (1-4) ◽  
pp. 117-147 ◽  
Author(s):  
A. kaplan ◽  
R. Tichatschke
Keyword(s):  
Convex Programming ◽  
Interior Point ◽  
Ill Posed

Minimum Vibration Mechanism Design via Convex Programming

2008 ◽  
Author(s):  
Bokman Lim ◽  
Frank C. Park ◽  
Seungjin Yoo
Keyword(s):  
Mechanism Design ◽  
Convex Programming ◽  
Natural Frequency ◽  
Interior Point ◽  
Design Methodology ◽  
Joint Stiffness ◽  
Convex Programming Problem ◽  
Closed Chain ◽  
Global Optima ◽  
Vibration Mechanism

One means of designing reduced vibration mechanisms is to ensure that the mechanism’s natural frequency be sufficiently greater than the driving frequencies of the actuators. In this paper we consider the problem of determining a mechanism’s mass, inertial, and joint stiffness parameters so as to maximize the lowest natural frequency of the mechanism. We show that this leads to a convex programming problem, which is characterized by global optima that can be found with efficient interior point algorithms. Several case studies involving closed chain mechanisms and hydraulically actuated excavators demonstrate the viability of the design methodology.

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