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Solving Reverse Convex Programming Problems Using a Generalized Cutting-Plane Method

机译:用广义切平面法求解反凸规划问题

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It is well known that each convex function f:Rn?R is supremally generated by affine functions. More precisely, each convex function f:Rn?R is the upper envelope of its affine minorants. In this paper, we propose an algorithm for solving reverse convex programming problems by using such a representation together with a generalized cutting-plane method. Indeed, by applying this representation, we solve a sequence of problems with a smaller feasible set, in which the reverse convex constraint is replaced by a still reverse convex but polyhedral constraint. Moreover, we prove that the proposed algorithm converges, under suitable assumptions, to an optimal solution of the original problem. This algorithm is coded in MATLAB language and is evaluated by some numerical examples.
机译:众所周知,每个凸函数f:Rn≥R都是由仿射函数产生的。更准确地说,每个凸函数f:Rn?R是其仿射少数的上包络线。在本文中,我们提出了一种通过使用这种表示形式和广义切平面方法来解决反向凸规划问题的算法。确实,通过应用这种表示,我们用较小的可行集解决了一系列问题,其中反向凸约束被仍然是反向凸但多面体约束代替。此外,我们证明了所提出的算法在适当的假设下收敛于原始问题的最优解。该算法以MATLAB语言编写,并通过一些数值示例进行了评估。

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