Strong Convergence on the Aggregate Constraint-Shifting Homotopy Method for Solving General Nonconvex Programming
Joint Authors
Zhu, Zhichuan
Liou, Yeong-Cheng
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-15
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
In the paper, the aggregate constraint-shifting homotopy method for solving general nonconvex nonlinear programming is considered.
The aggregation is only about inequality constraint functions.
Without any cone condition for the constraint functions, the existence and convergence of the globally convergent solution to the K-K-T system are obtained for both feasible and infeasible starting points under much weaker conditions.
American Psychological Association (APA)
Zhu, Zhichuan& Liou, Yeong-Cheng. 2020. Strong Convergence on the Aggregate Constraint-Shifting Homotopy Method for Solving General Nonconvex Programming. Journal of Mathematics،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1188260
Modern Language Association (MLA)
Zhu, Zhichuan& Liou, Yeong-Cheng. Strong Convergence on the Aggregate Constraint-Shifting Homotopy Method for Solving General Nonconvex Programming. Journal of Mathematics No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1188260
American Medical Association (AMA)
Zhu, Zhichuan& Liou, Yeong-Cheng. Strong Convergence on the Aggregate Constraint-Shifting Homotopy Method for Solving General Nonconvex Programming. Journal of Mathematics. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1188260
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1188260
