Global Optimization for Generalized Geometric Programs with Mixed Free-Sign Variables
成果类型：
Article
署名作者：
Li, Han-Lin; Lu, Hao-Chun
署名单位：
National Yang Ming Chiao Tung University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1080.0586
发表日期：
2009
页码：
701-713
关键词：
摘要：
Many optimization problems are formulated as generalized geometric programming (GGP) containing signomial terms f(X) . g(Y), where X and Y are continuous and discrete free-sign vectors, respectively. By effectively convexifying f(X) and linearizing g(Y), this study globally solves a GGP with a lower number of binary variables than are used in current GGP methods. Numerical experiments demonstrate the computational efficiency of the proposed method.