Global Optimization for Solving Linear Multiplicative Programming Based on a New Linearization Method
Joint Authors
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-31
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper presents a new global optimization algorithm for solving a class of linear multiplicative programming (LMP) problem.
First, a new linear relaxation technique is proposed.
Then, to improve the convergence speed of our algorithm, two pruning techniques are presented.
Finally, a branch and bound algorithm is developed for solving the LMP problem.
The convergence of this algorithm is proved, and some experiments are reported to illustrate the feasibility and efficiency of this algorithm.
American Psychological Association (APA)
Wang, Chun-Feng& Bai, Yan-Qin. 2016. Global Optimization for Solving Linear Multiplicative Programming Based on a New Linearization Method. Scientific Programming،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1118176
Modern Language Association (MLA)
Wang, Chun-Feng& Bai, Yan-Qin. Global Optimization for Solving Linear Multiplicative Programming Based on a New Linearization Method. Scientific Programming No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1118176
American Medical Association (AMA)
Wang, Chun-Feng& Bai, Yan-Qin. Global Optimization for Solving Linear Multiplicative Programming Based on a New Linearization Method. Scientific Programming. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1118176
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118176