Delays in payments have become a common risk factor for industrial projects, especially in recent years, since the financial position of firms has been threatened by pandemics, wars, inflation, and major supply chain disruptions. These delays create a time lag between expenses and payments, potentially leading to cash shortages that can have significant negative effects on the project success. To address cash shortage issues, project contractors often explore alternative financing options. The amount of money the contractor needs to borrow and when the loan is taken out considerably affects the overall project cost. In this paper, we present a distributionally robust model for effective cash flow management that minimizes the financing cost by accurately estimating the amount and timing of the expenses and revenues throughout the project life cycle. For the proposed model, we develop a heuristic algorithm that solves the problem efficiently. The performance of the heuristic is compared to the best-known solutions generated within a time limit by an off-the-shelf exact solver. Our results show that our algorithm is very competitive and can generate better solutions in substantially less time.

中文翻译：

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用于解决付款延迟问题的风险规避分布式鲁棒项目调度模型


付款延迟已成为工业项目的常见风险因素，尤其是近年来，因为企业的财务状况受到流行病、战争、通货膨胀和重大供应链中断的威胁。这些延误造成支出和付款之间的时间滞后，可能导致现金短缺，从而对项目的成功产生重大负面影响。为了解决现金短缺问题，项目承包商经常探索替代融资方案。承包商需要借款的金额以及何时提取贷款会极大地影响整个项目成本。在本文中，我们提出了一个用于有效现金流管理的分布稳健模型，该模型通过准确估计整个项目生命周期中费用和收入的金额和时间来最大限度地降低融资成本。对于所提出的模型，我们开发了一种启发式算法，可以有效地解决问题。将启发式的性能与现成的精确求解器在规定时间内生成的最著名的解决方案进行比较。我们的结果表明，我们的算法非常有竞争力，可以在更短的时间内生成更好的解决方案。