Constrained global optimization: algorithms and applications
Constrained global optimization: algorithms and applications
Zero duality gap for a class of nonconvex optimization problems
Journal of Optimization Theory and Applications
Convexification of a noninferior frontier
Journal of Optimization Theory and Applications
Local convexification of the Lagrangian function in nonconvex optimization
Journal of Optimization Theory and Applications
Journal of Global Optimization
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Global optimization of signomial mixed-integer nonlinear programming problems with free variables
Journal of Global Optimization
A review of recent advances in global optimization
Journal of Global Optimization
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A kind of general convexification and concavification methods is proposed for solving some classes of global optimization problems with certain monotone properties. It is shown that these minimization problems can be transformed into equivalent concave minimization problem or reverse convex programming problem or canonical D.C. programming problem by using the proposed convexification and concavification schemes. The existing algorithms then can be used to find the global solutions of the transformed problems.