Receivable financing is the process whereby cash is advanced to firms against receivables their customers have yet to pay: a receivable can be sold to a funder, which immediately gives the firm cash in return for a small percentage of the receivable amount as a fee. Receivable financing has been traditionally handled in a centralized way, where every request is processed by the funder individually and independently of one another. In this work we propose a novel, network-based approach to receivable financing, which enables customers of the same funder to autonomously pay each other as much as possible, and gives benefits to both the funder (reduced cash anticipation and exposure risk) and its customers (smaller fees and lightweight service establishment). Our main contributions consist in providing a principled formulation of the network-based receivable-settlement strategy, and showing how to achieve all algorithmic challenges posed by the design of this strategy. We formulate network-based receivable financing as a novel combinatorial-optimization problem on a multigraph of receivables. We show that the problem is NP-hard, and devise an exact branch-and-bound algorithm, as well as algorithms to efficiently find effective approximate solutions. Our more efficient algorithms are based on cycle enumeration and selection, and exploit a theoretical characterization in terms of a knapsack problem, as well as a refining strategy that properly adds paths between cycles. We also investigate the real-world issue of avoiding temporary violations of the problem constraints, and design methods for handling it. An extensive experimental evaluation is performed on real receivable data. Results attest the good performance of our methods.

中文翻译：

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连接的力量：利用网络分析推进应收账款融资

应收账款融资是根据客户尚未支付的应收账款向公司预付现金的过程：应收账款可以出售给资助者，资助者立即向公司提供现金，以换取应收账款金额的一小部分作为费用。应收融资传统上以集中方式处理，其中每个请求都由资助者单独且相互独立地处理。在这项工作中，我们提出了一种新颖的、基于网络的应收账款融资方法，它使同一资助者的客户能够尽可能多地自主支付，并使资助者受益（降低现金预期和敞口风险）及其客户（较低的费用和轻量级的服务机构）。我们的主要贡献包括提供基于网络的应收账款结算策略的原则性表述，并展示如何解决该策略设计带来的所有算法挑战。我们将基于网络的应收账款融资制定为一个新的应收账款多重图上的组合优化问题。我们证明该问题是 NP-hard 问题，并设计了一个精确的分支定界算法，以及有效找到有效近似解的算法。我们更有效的算法基于循环枚举和选择，并利用背包问题方面的理论表征，以及在循环之间适当添加路径的改进策略。我们还调查了避免暂时违反问题约束的现实问题，以及处理它的设计方法。对真实的应收数据进行了广泛的实验评估。结果证明了我们方法的良好性能。