A robust algorithm for generalized geometric programming
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- Shen, P., Ma, Y. & Chen, Y. J Glob Optim (2008) 41: 593. doi:10.1007/s10898-008-9283-0
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Most existing methods of global optimization for generalized geometric programming (GGP) actually compute an approximate optimal solution of a linear or convex relaxation of the original problem. However, these approaches may sometimes provide an infeasible solution, or far from the true optimum. To overcome these limitations, a robust solution algorithm is proposed for global optimization of (GGP) problem. This algorithm guarantees adequately to obtain a robust optimal solution, which is feasible and close to the actual optimal solution, and is also stable under small perturbations of the constraints.