Vahdani Behnam, Mohammadi Mehrdad, Thevenin Simon, Meyer Patrick, Dolgui Alexandre
IMT Atlantique, Lab-STICC, UMR CNRS 6285, Brest F-29238, France.
Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven 5600MB, the Netherlands.
Omega. 2023 Oct;120:102909. doi: 10.1016/j.omega.2023.102909. Epub 2023 Jun 4.
The COVID-19 virus's high transmissibility has resulted in the virus's rapid spread throughout the world, which has brought several repercussions, ranging from a lack of sanitary and medical products to the collapse of medical systems. Hence, governments attempt to re-plan the production of medical products and reallocate limited health resources to combat the pandemic. This paper addresses a multi-period production-inventory-sharing problem (PISP) to overcome such a circumstance, considering two consumable and reusable products. We introduce a new formulation to decide on production, inventory, delivery, and sharing quantities. The sharing will depend on net supply balance, allowable demand overload, unmet demand, and the reuse cycle of reusable products. Undeniably, the dynamic demand for products during pandemic situations must be reflected effectively in addressing the multi-period PISP. A bespoke compartmental susceptible-exposed-infectious-hospitalized-recovered-susceptible (SEIHRS) epidemiological model with a control policy is proposed, which also accounts for the influence of people's behavioral response as a result of the knowledge of adequate precautions. An accelerated Benders decomposition-based algorithm with tailored valid inequalities is offered to solve the model. Finally, we consider a realistic case study - the COVID-19 pandemic in France - to examine the computational proficiency of the decomposition method. The computational results reveal that the proposed decomposition method coupled with effective valid inequalities can solve large-sized test problems in a reasonable computational time and 9.88 times faster than the commercial Gurobi solver. Moreover, the sharing mechanism reduces the total cost of the system and the unmet demand on the average up to 32.98% and 20.96%, respectively.
新冠病毒的高传播性导致该病毒在全球迅速传播,引发了一系列影响,从卫生和医疗用品短缺到医疗系统崩溃。因此,各国政府试图重新规划医疗产品的生产,并重新分配有限的卫生资源以抗击疫情。本文针对这一情况,考虑两种消耗性和可重复使用的产品,研究了一个多周期生产 - 库存共享问题(PISP)。我们引入了一种新的公式来确定生产、库存、交付和共享数量。共享将取决于净供应平衡、允许的需求过载、未满足的需求以及可重复使用产品的再利用周期。不可否认,在应对多周期PISP时,必须有效反映疫情期间产品的动态需求。我们提出了一种带有控制策略的定制化易感染 - 暴露 - 感染 - 住院 - 康复 - 易感染(SEIHRS)流行病学模型,该模型还考虑了人们因了解充分预防措施而产生的行为反应的影响。我们提供了一种基于加速Benders分解并带有定制化有效不等式的算法来求解该模型。最后,我们考虑一个实际案例研究——法国的新冠疫情——来检验分解方法的计算效率。计算结果表明,所提出的分解方法结合有效的有效不等式能够在合理的计算时间内解决大型测试问题,并且比商业Gurobi求解器快9.88倍。此外,共享机制分别将系统总成本和未满足需求平均降低了32.98%和20.96%。