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Download Convexification and Global Optimization in Continuous and by Mohit Tawarmalani PDF

By Mohit Tawarmalani

Interest in restricted optimization originated with the easy linear seasoned­ gramming version because it used to be sensible and maybe the single computationally tractable version on the time. restricted linear optimization types have been quickly followed in several program components and are might be the main widespread mathematical versions in operations examine and administration technology on the time of this writing. Modelers have, besides the fact that, came across the idea of linearity to be overly restrictive in expressing the real-world phenomena and difficulties in economics, finance, company, verbal exchange, engineering layout, computational biology, and different components that often call for using nonlinear expressions and discrete variables in optimization versions. either one of those extensions of the linear programming version are NP-hard, therefore representing very not easy difficulties. at the brighter aspect, contemporary advances in algorithmic and computing know-how give the opportunity to re­ stopover at those issues of the wish of fixing essentially appropriate difficulties in moderate quantities of computational time. preliminary makes an attempt at fixing nonlinear courses focused on the de­ velopment of neighborhood optimization tools making certain globality less than the idea of convexity. nonetheless, the integer programming liter­ ature has targeting the improvement of equipment that ascertain international optima. the purpose of this ebook is to marry the developments in fixing nonlinear and integer programming types and to increase new leads to the extra common framework of mixed-integer nonlinear courses (MINLPs) with the objective of devising virtually effective international optimization algorithms for MINLPs.

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Extra resources for Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming: Theory, Algorithms, Software, and Applications

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Then, a convex extension of ¢ : C f--t lR restricted to UXEFIX can be constructed over C if and only if ¢ is convex over all X E F J . Further, the convex envelope of ¢ over C is one such convex extension. Proof. 8. o It should be noted that the convex envelope of ¢ over C is not necessarily the tightest convex extension of ¢ restricted to UXEFIX over C. This may be illustrated through a simple example. Consider the closed interval C = [0,1]. Let X be the set of its endpoints {O, I}. Further, let ¢ be x 2 .

2, F' = conv(<1>'), where <1>' is the epigraph of ¢(x) over X'. In other words, f(x) restricted to X' is the convex envelope of ¢ restricted to X'. 2. C. 5. Let X be a convex set. Assume that f(x) is the convex envelope of 4>( x) over X. Then f (x) = 4>( x) at extreme points of X. Proof. 4 as an extreme point of X is a non empty face of X. 0 We now provide a formal definition of convex extensions. This definition is a generalized version of those used by Crama (1993). 6. Let C be a convex set and X ~ C.

Let X be a closed convex set and X' be an n-dimensional face of X. Consider a convex function f : X 1---7 JR with epigraph F. There exists a face F' of F such that X' is the projection of F' onto aff(X) and dim(F') = n + 1. Proof. Let X' be expressed as X n M where M is an affine space. Consider F' = F n {(a, x) I a E JR, x E M}, the epigraph of f restricted to X'. We prove by contradiction that F' is a face of F. Assume F' is not a face of F. Then, there exists a closed line segment in F containing a point, say (XO, fO), that belongs to ri(F') and another point, say (xl, f1), that does not belong to F'.

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