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

Han-Lin Li () and Hao-Chun Lu ()
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Han-Lin Li: Institute of Information Management, National Chiao Tung University, Taiwan, Republic of China
Hao-Chun Lu: Institute of Information Management, National Chiao Tung University, Taiwan, Republic of China

Operations Research, 2009, vol. 57, issue 3, 701-713

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.

Keywords: programming; geometric; generalized geometric programming (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (16)

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