论文标题

在一致的流量限制下,强大的转运问题

Robust transshipment problem under consistent flow constraints

论文作者

Büsing, Christina, Koster, Arie M. C. A, Schmitz, Sabrina

论文摘要

储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。

In this paper, we study robust transshipment under consistent flow constraints. We consider demand uncertainty represented by a finite set of scenarios and characterize a subset of arcs as so-called fixed arcs. In each scenario, we require an integral flow that satisfies the respective flow balance constraints. In addition, on each fixed arc, we require equal flow for all scenarios. The objective is to minimize the maximum cost occurring among all scenarios. We show that the problem is strongly NP-hard on acyclic digraphs by a reduction from the $(3,B2)$-SAT problem. Furthermore, we prove that the problem is weakly NP-hard on series-parallel digraphs by a reduction from a special case of the \textsc{Partition} problem. If in addition the number of scenarios is constant, we observe the pseudo-polynomial-time solvability of the problem. We provide polynomial-time algorithms for three special cases on series-parallel digraphs. Finally, we present a polynomial-time algorithm for pearl digraphs.

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