Geometric programming based robot control design
ICC&IE '94 Proceedings of the 17th international conference on Computers and industrial engineering
Effectiveness of a geometric programming algorithm for optimization of machining economics models
Computers and Operations Research
An infeasible interior-point algorithm for solving primal and dual geometric programs
Mathematical Programming: Series A and B - Special issue: interior point methods in theory and practice
Global Optimization of Nonconvex Polynomial Programming Problems HavingRational Exponents
Journal of Global Optimization
A stochastic geometric programming problem with multiplicative recourse
Operations Research Letters
A robust algorithm for generalized geometric programming
Journal of Global Optimization
A nonisolated optimal solution for special reverse convex programming problems
Journal of Computational and Applied Mathematics
Computational Optimization and Applications
Mathematical and Computer Modelling: An International Journal
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In this paper a deterministic global optimization algorithm is proposed for locatingthe global minimum of the generalized geometric programming (GGP) problem. By utilizing an exponential variable transformation and some other techniques the initial nonconvex problem (GGP) is reduced to a typical reverse convex programming (RCP). Then a linear relaxation of problem (RCP) is obtained based on the famous arithmetic-geometric mean inequality and the linear upper bound of the reverse constraints inside some hyperrectangle region. The proposed branch and bound algorithm is convergent to the global minimum through the successive refinement of the linear relaxation of the feasible region of the objective function and the solutions of a series of linear optimization problems. And finally the numerical experiment is given to illustrate the feasibility and the robust stability of the present algorithm.