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...

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Main Authors: Zhao, Hui, Huang, Edward, Dou, Runliang, Wu, Kan
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/152090
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1520902021-07-14T08:59:10Z A multi-objective production planning problem with the consideration of time and cost in clinical trials Zhao, Hui Huang, Edward Dou, Runliang Wu, Kan School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Supply Chain Management Clinical Trial 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. Economic Development Board (EDB) This research is supported in part by the GSK-Singapore Partnership for Green and Sustainable Manufacturing under Grant M406884. 2021-07-14T08:59:10Z 2021-07-14T08:59:10Z 2019 Journal Article Zhao, H., Huang, E., Dou, R. & Wu, K. (2019). A multi-objective production planning problem with the consideration of time and cost in clinical trials. Expert Systems With Applications, 124, 25-38. https://dx.doi.org/10.1016/j.eswa.2019.01.038 0957-4174 https://hdl.handle.net/10356/152090 10.1016/j.eswa.2019.01.038 2-s2.0-85060281210 124 25 38 en M406884 Expert Systems with Applications © 2019 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Supply Chain Management
Clinical Trial
spellingShingle Engineering::Mechanical engineering
Supply Chain Management
Clinical Trial
Zhao, Hui
Huang, Edward
Dou, Runliang
Wu, Kan
A multi-objective production planning problem with the consideration of time and cost in clinical trials
description 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.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Zhao, Hui
Huang, Edward
Dou, Runliang
Wu, Kan
format Article
author Zhao, Hui
Huang, Edward
Dou, Runliang
Wu, Kan
author_sort Zhao, Hui
title A multi-objective production planning problem with the consideration of time and cost in clinical trials
title_short A multi-objective production planning problem with the consideration of time and cost in clinical trials
title_full A multi-objective production planning problem with the consideration of time and cost in clinical trials
title_fullStr A multi-objective production planning problem with the consideration of time and cost in clinical trials
title_full_unstemmed A multi-objective production planning problem with the consideration of time and cost in clinical trials
title_sort multi-objective production planning problem with the consideration of time and cost in clinical trials
publishDate 2021
url https://hdl.handle.net/10356/152090
_version_ 1707050435222700032