Journal of Global Optimization
Tight convex underestimators for $${{\mathcal C}^2}$$-continuous problems: I. univariate functions
Journal of Global Optimization
A review of recent advances in global optimization
Journal of Global Optimization
Convex relaxation for solving posynomial programs
Journal of Global Optimization
On convex relaxations of quadrilinear terms
Journal of Global Optimization
Generalized McCormick relaxations
Journal of Global Optimization
Compact relaxations for polynomial programming problems
SEA'12 Proceedings of the 11th international conference on Experimental Algorithms
Deterministic global optimization in ab-initio quantum chemistry
Journal of Global Optimization
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Convex envelopes of nonconvex functions are widely used to calculate lower bounds to solutions of nonlinear programming problems (NLP), particularly within the context of spatial Branch-and-Bound methods for global optimization. This paper proposes a nonlinear continuous and differentiable convex envelope for monomial terms of odd degree, x2k+1, where k ∈ N and the range of x includes zero. We prove that this envelope is the tightest possible. We also derive a linear relaxation from the proposed envelope, and compare both the nonlinear and linear formulations with relaxations obtained using other approaches.