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首页> 外文期刊>Mathematical Programming >SPEEDING UP KARMARKARS ALGORITHM FOR MULTICOMMODITY FLOWS
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SPEEDING UP KARMARKARS ALGORITHM FOR MULTICOMMODITY FLOWS

机译:加快多商品流的KARMARKARS算法

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摘要

We show how to speed up Karmarkar's linear programming algorithm for the case of multicommodity hows. The special structure of the constraint matrix is exploited to obtain an algorithm for the multicommodity flow problem which requires O(s(3.5)v(2.5)eL) arithmetic operations, each operation being performed to a precision of O(L) bits. Here v is the number of vertices and e is the number of edges in the given network, s is the number of commodities, and L is bounded by the number of bits in the input. We obtain a speed up of the order of (e(0.5)/v(0.5)) + (e(2.5)/v(2.5)s(2)) over Karmarkar's modified algorithm which is substantial for dense networks. The techniques in the paper can also be used to speed up any interior point algorithm for any linear programming problem whose constraint matrix is structurally similar to the one in the multicommodity flow problem. [References: 14]
机译:我们展示了如何在多商品方法的情况下加快Karmarkar的线性规划算法。利用约束矩阵的特殊结构来获得针对多商品流问题的算法,该算法需要O(s(3.5)v(2.5)eL)算术运算,每个运算的执行精度为O(L)位。这里v是顶点数,e是给定网络中的边数,s是商品数,L由输入中的位数限制。我们通过Karmarkar的改进算法获得了(e(0.5)/ v(0.5))+(e(2.5)/ v(2.5)s(2))数量级的加速,该算法对于密集网络非常重要。本文中的技术还可以用于加速任何线性规划问题的内点算法,该线性规划问题的约束矩阵在结构上与多商品流问题中的约束矩阵相似。 [参考:14]

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