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Efficient algorithms for separated continuous linear programs: The multicommodity flow problem with holding costs and extensions

机译:分离连续线性程序的有效算法:持有成本和延期的多商品流问题

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We give an approximation scheme for separated continuous linear programming problems. Such problems arise as fluid relaxations of multiclass queueing networks and are used to find approximate solutions to complex job shop scheduling problems. In a network with linear flow costs and linear, per-unit-time holding costs, our algorithm finds a drainage of the network that, for given constants epsilon > 0 and delta > 0, has total cost (1 + epsilon)OPT + delta, where OPT is the cost of the minimum cost drainage. The complexity of our algorithm is polynomial in the size of the input network, 1/epsilon, and log(1/delta). The fluid relaxation is a continuous problem. While the problem is known to have a piecewise constant solution, it is not known to have a polynomially sized solution. We introduce a natural discretization of polynomial size and prove that this discretization produces a solution with low cost. This is the first polynomial time algorithm with a provable approximation guarantee for fluid relaxations.
机译:对于分离的连续线性规划问题,我们给出一个近似方案。此类问题是由于多类排队网络的流动性松弛而引起的,并用于找到复杂的车间调度问题的近似解决方案。在具有线性流量成本和线性,每单位时间持有成本的网络中,我们的算法发现对于给定常数epsilon> 0和delta> 0,总成本为(1 + epsilon)OPT + delta的网络排水情况,其中OPT是最低费用支出的费用。我们算法的复杂性是输入网络的大小,1 /ε和log(1 / delta)的多项式。流体松弛是一个连续的问题。虽然已知该问题具有分段常数解,但尚不知道具有多项式大小的解。我们引入了多项式大小的自然离散化方法,并证明了这种离散化方法可以产生低成本的解决方案。这是第一个多项式时间算法,具有可证明的流体松弛近似保证。

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