Global optimization algorithm for a generalized linear multiplicative programming

2012 ◽  
Vol 40 (1-2) ◽  
pp. 551-568 ◽  
Author(s):  
Hongwei Jiao ◽  
Sanyang Liu ◽  
Yongqiang Chen
2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Chun-Feng Wang ◽  
Yan-Qin Bai

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.


2017 ◽  
Vol 13 (3) ◽  
pp. 587-596
Author(s):  
S. Batbileg ◽  
N. Tungalag ◽  
A. Anikin ◽  
A. Gornov ◽  
E. Finkelstein

Measurement ◽  
2019 ◽  
Vol 134 ◽  
pp. 253-265
Author(s):  
Tao Ye ◽  
Xi Zhang ◽  
Ping Song ◽  
Fei Yang

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