Titlebook: Quasiconvex Optimization and Location Theory; Jaoquim António Santos Gromicho Book 19981st edition Kluwer Academic Publishers 1998 algorit

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Introduction,d as minimizing or maximizing an . subject to a family of .. The choice of which functions to use as an objective function and as constraints depends on the . of the problem. However, modeling a problem is only useful in practice if there exist methods to solve the proposed model. This justifies the

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Quasiconvex Programming, possible to construct a hyperplane separating a given point from its corresponding strict lower level set. In spite of the convexity of this set such a “computable” separation is not a trivial matter for a quasiconvex function. Therefore, Section 5.2, based on Ref. [39], is devoted to this topic. T

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Introduction,hod, the popular simplex method, exists since the late forties to solve these problems. In spite of this, there are many real life situations which cannot be appropriately modeled using only linear functions and therefore the field of . has received increasing attention from many researchers.

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