Aggregate Homotopy Method for Min-Max-Min Programming Satisfying a Weak-Normal Cone Condition

Abstract:

Article Preview

Min-max-min programming is an important but difficult nonsmooth programming. An aggregate homotopy method was given for solving min-max-min programming by Bo Yu el al. However, the method requires a difficult to verify weak-normal cone condition. Moreover, the method is only theoretically with no algorithmic implementation. In this paper, the weak normal cone condition is discussed first. A class of min-max-min programming satisfying the condition is introduced. A detailed algorithm to implement the method is presented. Models arising from some applications such as support vector machine for multiple-instance classification in data mining, can be included in the problem. In the end, the aggregate homotopy method is given to solve the multiple-instance support vector machine model.

Info:

Periodical:

Edited by:

Shaobo Zhong, Yimin Cheng and Xilong Qu

Pages:

669-672

DOI:

10.4028/www.scientific.net/AMM.50-51.669

Citation:

H. J. Xiong and B. Yu, "Aggregate Homotopy Method for Min-Max-Min Programming Satisfying a Weak-Normal Cone Condition", Applied Mechanics and Materials, Vols. 50-51, pp. 669-672, 2011

Online since:

February 2011

Authors:

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.