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Proximal Point Algorithms for Vector DC Programming with Applications to Probabilistic Lot Sizing with Service Levels
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-31
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
We present a new algorithm for solving vector DC programming, where the vector function is a function of the difference of C-convex functions.
Because of the nonconvexity of the objective function, it is difficult to solve this class of problems.
We propose several proximal point algorithms to address this class of problems, which make use of the special structure of the problems (i.e., the DC structure).
The well-posedness and the global convergence of the proposed algorithms are developed.
The efficiency of the proposed algorithm is shown by an application to a multicriteria model stemming from lot sizing problems.
American Psychological Association (APA)
Ji, Ying& Qu, Shaojian. 2017. Proximal Point Algorithms for Vector DC Programming with Applications to Probabilistic Lot Sizing with Service Levels. Discrete Dynamics in Nature and Society،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1151555
Modern Language Association (MLA)
Ji, Ying& Qu, Shaojian. Proximal Point Algorithms for Vector DC Programming with Applications to Probabilistic Lot Sizing with Service Levels. Discrete Dynamics in Nature and Society No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1151555
American Medical Association (AMA)
Ji, Ying& Qu, Shaojian. Proximal Point Algorithms for Vector DC Programming with Applications to Probabilistic Lot Sizing with Service Levels. Discrete Dynamics in Nature and Society. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1151555
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1151555