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Abstract and Applied Analysis
Volume 2014 (2014), Article ID 163263, 12 pages
Research Article

A Global Optimization Algorithm for Signomial Geometric Programming Problem

College of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, China

Received 17 December 2013; Accepted 16 January 2014; Published 30 March 2014

Academic Editor: Yisheng Song

Copyright © 2014 Xue-Ping Hou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a global optimization algorithm for solving the signomial geometric programming (SGP) problem. In the algorithm, by the straight forward algebraic manipulation of terms and by utilizing a transformation of variables, the initial nonconvex programming problem (SGP) is first converted into an equivalent monotonic optimization problem and then is reduced to a sequence of linear programming problems, based on the linearizing technique. To improve the computational efficiency of the algorithm, two range reduction operations are combined in the branch and bound procedure. The proposed algorithm is convergent to the global minimum of the (SGP) by means of the subsequent solutions of a series of relaxation linear programming problems. And finally, the numerical results are reported to vindicate the feasibility and effectiveness of the proposed method.