Incorporation Competence Sets of Decision Makers by Deduction Graphs
Operations Research
Treating Free Variables in Generalized Geometric Global Optimization Programs
Journal of Global Optimization
Digital Circuit Optimization via Geometric Programming
Operations Research
A Superior Representation Method for Piecewise Linear Functions
INFORMS Journal on Computing
A DIAMOND method of inducing classification rules for biological data
Computers in Biology and Medicine
A DIAMOND method for classifying biological data
ICMB'10 Proceedings of the Second international conference on Medical Biometrics
Base-2 Expansions for Linearizing Products of Functions of Discrete Variables
Operations Research
Base-2 Expansions for Linearizing Products of Functions of Discrete Variables
Operations Research
INFORMS Journal on Computing
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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.