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Maximizing for the sum of ratios of two convex functions over a convex set

机译:最大化凸集上两个凸函数的比率之和

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This paper presents an algorithm for globally maximizing a sum of convex-convex ratios problem with a convex feasible region, which does not require involving all the functions to be differentiable and requires that their sub-gradients can be calculated efficiently. To our knowledge, little progress has been made for globally solving this problem so far. The algorithm uses a branch and bound scheme in which the main computational effort involves solving a sequence of linear programming subproblems. Because of these properties, the algorithm offers a potentially attractive means for globally solving the sum of convex-convex ratios problem over a convex feasible region. It has been proved that the algorithm possesses global convergence. Finally, the numerical experiments are given to show the feasibility of the proposed algorithm.
机译:本文提出了一种全局可行的最大化具有凸可行区域的凸-凸比率问题的算法,该算法不需要使所有函数都可微,并且要求可以有效地计算它们的子梯度。据我们所知,到目前为止,在全球范围内解决该问题进展甚微。该算法使用分支定界方案,其中主要的计算工作涉及解决一系列线性规划子问题。由于这些特性,该算法为整体解决凸可行区域上的凸-凸比率问题之和提供了一种潜在的有吸引力的手段。证明了该算法具有全局收敛性。最后,通过数值实验证明了该算法的可行性。

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