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首页> 外文期刊>Journal of combinatorial optimization >Efficient Algorithms and Implementations for Optimizing the Sum of Linear Fractional Functions, with Applications
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Efficient Algorithms and Implementations for Optimizing the Sum of Linear Fractional Functions, with Applications

机译:用于优化线性分数函数和的高效算法和实现,及其应用

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摘要

This paper presents an improved algorithm for solving the sum of linear fractional functions (SOLF) problem in 1-D and 2-D. A key subproblem to our solution is the off-line ratio query (OLRQ) problem, which asks to find the optimal values of a sequence of m linear fractional functions (called ratios), each ratio subject to a feasible domain defined by O(n) linear constraints. Based on some geometric properties and the parametric linear programming technique, we develop an algorithm that solves the OLRQ problem in O((m+n)log (m+n)) time. The OLRQ algorithm can be used to speed up every iteration of a known iterative SOLF algorithm, from O(m(m+n)) time to O((m+n)log (m+n)), in 1-D and 2-D. Implementation results of our improved 1-D and 2-D SOLF algorithm have shown that in most cases it outperforms the commonly-used approaches for the SOLF problem. We also apply our techniques to some problems in computational geometry and other areas, improving the previous results.
机译:本文提出了一种改进的算法来解决一维和二维线性分数函数(SOLF)问题。我们解决方案的一个关键子问题是离线比率查询(OLRQ)问题,该问题要求找到m个线性分数函数(称为比率)序列的最优值,每个比率服从由O(n )线性约束。基于一些几何性质和参数线性规划技术,我们开发了一种算法,可以解决O((m + n)log(m + n))时间内的OLRQ问题。 OLRQ算法可用于加速已知迭代SOLF算法的每次迭代,从O(m(m + n))时间到O((m + n)log(m + n)),在1-D和二维我们改进的一维和二维SOLF算法的实现结果表明,在大多数情况下,它的性能都优于解决SOLF问题的常用方法。我们还将我们的技术应用于计算几何和其他领域中的某些问题,从而改善了先前的结果。

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