Lotfi Reza, Kheiri Kiana, Sadeghi Ali, Babaee Tirkolaee Erfan
Department of Industrial Engineering, Yazd University, Yazd, Iran.
Behineh Gostar Sanaye Arman, Tehran, Iran.
Ann Oper Res. 2022 Jan 6:1-25. doi: 10.1007/s10479-021-04490-6.
This research develops a regression-based Robust Optimization (RO) approach to efficiently predict the number of patients with confirmed infection caused by the recent Coronavirus Disease (COVID-19). The main idea is to study the dynamics of the COVID-19 outbreak at the first stage and then provide efficient insights to estimate the necessary resources accordingly. The convex RO with Mean Absolute Deviation (MAD) objective function is utilized to project the course of COVID-19 epidemic in Iran. To validate the performance of the suggested model, a real-case study is investigated and compared to several well-known forecasting models including Simple Moving Average, Exponential Moving Average, Weighted Moving Average and Exponential Smoothing with Trend Adjustment models. Furthermore, the effect of parameter uncertainties is examined using a set of sensitivity analyses. The results demonstrate that by increasing the degree (coefficient) of regression up to 8, MAD value decreases to 1378.12, and consequently, the corresponding equation becomes more accurate. On the other hand, from the 8th degree onwards, MAD value follows an upward trend. Furthermore, by increasing the level of regression uncertainty, MAD value follows a downward trend to reach 1309.28 and the estimation accuracy of the model increases accordingly. Finally, our proposed model achieves the least MAD and the greatest correlation coefficient against the other models.
本研究开发了一种基于回归的稳健优化（RO）方法，以有效预测近期由冠状病毒病（COVID-19）导致的确诊感染患者数量。主要思路是在第一阶段研究COVID-19疫情的动态，然后据此提供有效见解以估计所需资源。利用具有平均绝对偏差（MAD）目标函数的凸RO来预测伊朗COVID-19疫情的发展过程。为验证所提模型的性能，开展了一项实际案例研究，并与包括简单移动平均、指数移动平均、加权移动平均以及趋势调整指数平滑模型在内的几种知名预测模型进行比较。此外，使用一组敏感性分析来检验参数不确定性的影响。结果表明，将回归度（系数）提高到8时，MAD值降至1378.12，相应方程因此变得更准确。另一方面，从第8度起，MAD值呈上升趋势。此外，随着回归不确定性水平的提高，MAD值呈下降趋势，降至1309.28，模型的估计准确性相应提高。最后，与其他模型相比，我们提出的模型实现了最小的MAD和最大的相关系数。
