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Global Optimization for Generalized Geometric Programs with Mixed Free-Sign Variables

Institute of Information Management, National Chiao Tung University, Taiwan, Republic of China
Institute of Information Management, National Chiao Tung University, Taiwan, Republic of China
hlli{at}cc.nctu.edu.tw
haoclu{at}gmail.com

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.

Subject classifications: programming; geometric; generalized geometric programming.
History: Received October 2006; revision received October 2007; accepted January 2008.