Introduction to non-linear optimization
Introduction to non-linear optimization
Constrained global optimization: algorithms and applications
Constrained global optimization: algorithms and applications
Introduction to optimization
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Canonical DC programming problem: Outer approximation methods revisited
Operations Research Letters
Journal of Global Optimization
Computational Optimization and Applications
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D.c. functions are functions that can be expressed as the sum of a concave function and a convex function (or as the difference of two convex functions). In this paper, we extend the class of univariate functions that can be represented as d.c. functions. This expanded class is very broad including a large number of nonlinear and/or ’nonsmooth‘ univariate functions. In addition, the procedure specifies explicitly the functional and numerical forms of the concave and convex functions that comprise the d.c. representation of the univariate functions. The procedure is illustrated using two numerical examples. Extensions of the conversion procedure for discontinuous univariate functions is also discussed.