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Solving the sum-of-ratios problem by a stochastic search algorithm

机译:用随机搜索算法解决比率总和问题

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In spite of the recent progress in fractional programming, the sum-of-ratios problem remains untoward. Freund and Jarre proved that this is an NP-complete problem. Most methods overcome the difficulty using the deterministic type of algorithms, particularly, the branch-and-bound method. In this paper, we propose a new approach by applying the stochastic search algorithm introduced by Birbil, Fang and Sheu to a transformed image space. The algorithm then computes and moves sample particles in the q - 1 dimensional image space according to randomly controlled interacting electromagnetic forces. Numerical experiments on problems up to sum of eight linear ratios with a thousand variables are reported. The results also show that solving the sum-of-ratios problem in the image space as proposed is, in general, preferable to solving it directly in the primal domain.
机译:尽管最近在分数程序设计方面取得了进展,但是比率总和问题仍然不可行。 Freund和Jarre证明这是一个NP完全问题。大多数方法克服了使用确定性算法的困难,尤其是分支定界方法。在本文中,我们通过将Birbil,Fang和Sheu引入的随机搜索算法应用于变换后的图像空间,提出了一种新方法。然后,该算法根据随机控制的相互作用电磁力在q-1维图像空间中计算并移动样本粒子。报道了对多达八千个具有一千个变量的线性比率之和的问题的数值实验。结果还表明,一般而言,解决所提出的图像空间中的比率总和问题优于直接在原始域中解决问题。

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