Rios-Solis Yasmin Agueda, Saucedo-Espinosa Mario Alberto, Caballero-Robledo Gabriel Arturo
Systems Engineering, Universidad Autónoma de Nuevo León, Monterrey, Nuevo León, Mexico.
Rochester Institute of Technology, Microsystems Engineering Department, Rochester, United States of America.
PLoS One. 2017 Apr 21;12(4):e0175782. doi: 10.1371/journal.pone.0175782. eCollection 2017.
The Repayment Policy for Multiple Loans is about a given set of loans and a monthly incoming cash flow: what is the best way to allocate the monthly income to repay such loans? In this article, we close the almost 20-year-old open question about how to model the repayment policy for multiple loans problem together with its computational complexity. Thus, we propose a mixed integer linear programming model that establishes an optimal repayment schedule by minimizing the total amount of cash required to repay the loans. We prove that the most employed repayment strategies, such as the highest interest debt and the debt snowball methods, are not optimal. Experimental results on simulated cases based on real data show that our methodology obtains on average more than 4% of savings, that is, the debtor pays approximately 4% less to the bank or loaner, which is a considerable amount in finances. In certain cases, the debtor can save up to 40%.
如何将每月收入分配用于偿还此类贷款才是最佳方式？在本文中，我们解决了一个近20年的开放性问题，即如何对多笔贷款问题的还款策略进行建模及其计算复杂性。因此，我们提出了一个混合整数线性规划模型，该模型通过最小化偿还贷款所需的现金总额来建立最优还款计划。我们证明，最常用的还款策略，如最高利息债务和债务雪球法，并非最优。基于真实数据的模拟案例实验结果表明，我们的方法平均可节省超过4%，即债务人向银行或贷款人支付的金额减少约4%，这在金融领域是一笔可观的数额。在某些情况下，债务人最多可节省40%。
