Title: Global Optimization for Generalized Geometric Programs with Mixed Free-Sign Variables
Authors: Li, Han-Lin
Lu, Hao-Chun
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
Issue Date: 1-May-2009
Abstract: 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.
URI: http://dx.doi.org/10.1287/opre.1080.0586
ISSN: 0030-364X
DOI: 10.1287/opre.1080.0586
Volume: 57
Issue: 3
Begin Page: 701
End Page: 713
Appears in Collections:Articles