A multi-objective production planning problem with the consideration of time and cost in clinical trials

Under increasingly challenging circumstances, pharmaceutical companies try to reduce the overproduction of clinical drugs, which is commonly seen in the pharmaceutical industry. When the overproduction is simply reduced without an efficient coordination of the inventories in the supply chain, the st...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Zhao, Hui, Huang, Edward, Dou, Runliang, Wu, Kan
مؤلفون آخرون: School of Mechanical and Aerospace Engineering
التنسيق: مقال
اللغة:English
منشور في: 2021
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/152090
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص:Under increasingly challenging circumstances, pharmaceutical companies try to reduce the overproduction of clinical drugs, which is commonly seen in the pharmaceutical industry. When the overproduction is simply reduced without an efficient coordination of the inventories in the supply chain, the stock-outs at clinical sites and clinical trial delay can hardly be avoided. In this study, we propose a multi-objective model to optimize the production quantity, where the clinical trial duration and the total production and operational costs are minimized. The problem is formulated as a multi-stage stochastic programming model to capture the dynamic inventory allocation process in the supply chains. Since this problem's solving time and required memory can increase significantly with the increase of the stage and scenario numbers, the progressive hedging algorithm is applied as the solution approach in this paper. In the numerical experiments, we study this algorithm's performance and compare the solving efficiency with the direct solution approach. In addition, we identify the optimal production quantity of clinical drugs and give a discussion about the tradeoffs between the clinical trial delay and total cost.