A bi-level multi-follower optimization model for R&D project portfolio: an application to a pharmaceutical holding company
The need for a study of project portfolio optimization in pharmaceutical R&D has become all the more urgent with the outbreak of COVID-19. This study examines a new model for optimizing R&D project portfolios under a decentralized decision-making structure in a pharmaceutical holding company...
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Veröffentlicht in: | Annals of operations research 2023-04, Vol.323 (1-2), p.331-360 |
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creator | Salehi, Faraz Mirzapour Al-E-Hashem, S. Mohammad J. Moattar Husseini, S. Mohammad Ghodsypour, S. Hassan |
description | The need for a study of project portfolio optimization in pharmaceutical R&D has become all the more urgent with the outbreak of COVID-19. This study examines a new model for optimizing R&D project portfolios under a decentralized decision-making structure in a pharmaceutical holding company. Specifically, two levels of decision makers hierarchically decide on budget allocation and project portfolio selection-scheduling to maximize their profit, and we formulate the problem as a bi-level multi-follower mixed-integer optimization model. At the upper level, the investment company has complete knowledge of the subsidiaries' response, acts first, and decides on the best budget allocation. At the lower level, each subsidiary responds to the allocated budget and decides on its portfolio scheduling. Since the lower level represents several mixed-integer programming problems, solving the resulting bi-level model is challenging. Therefore, we propose an efficient hybrid solution approach based on parametric optimization and convert the bi-level model into a single-level mixed-integer model. To validate it, we solve a case and discuss the optimal strategy of each actor. The experimental results show that the planned project portfolio for each subsidiary of the holding company is drastically affected by the allocated budget and its decisions. |
doi_str_mv | 10.1007/s10479-022-05052-0 |
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At the lower level, each subsidiary responds to the allocated budget and decides on its portfolio scheduling. Since the lower level represents several mixed-integer programming problems, solving the resulting bi-level model is challenging. Therefore, we propose an efficient hybrid solution approach based on parametric optimization and convert the bi-level model into a single-level mixed-integer model. To validate it, we solve a case and discuss the optimal strategy of each actor. 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Mohammad J.</creatorcontrib><creatorcontrib>Moattar Husseini, S. Mohammad</creatorcontrib><creatorcontrib>Ghodsypour, S. Hassan</creatorcontrib><title>A bi-level multi-follower optimization model for R&D project portfolio: an application to a pharmaceutical holding company</title><title>Annals of operations research</title><addtitle>Ann Oper Res</addtitle><addtitle>Ann Oper Res</addtitle><description>The need for a study of project portfolio optimization in pharmaceutical R&D has become all the more urgent with the outbreak of COVID-19. This study examines a new model for optimizing R&D project portfolios under a decentralized decision-making structure in a pharmaceutical holding company. Specifically, two levels of decision makers hierarchically decide on budget allocation and project portfolio selection-scheduling to maximize their profit, and we formulate the problem as a bi-level multi-follower mixed-integer optimization model. At the upper level, the investment company has complete knowledge of the subsidiaries' response, acts first, and decides on the best budget allocation. At the lower level, each subsidiary responds to the allocated budget and decides on its portfolio scheduling. Since the lower level represents several mixed-integer programming problems, solving the resulting bi-level model is challenging. Therefore, we propose an efficient hybrid solution approach based on parametric optimization and convert the bi-level model into a single-level mixed-integer model. To validate it, we solve a case and discuss the optimal strategy of each actor. 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Mohammad J.</au><au>Moattar Husseini, S. Mohammad</au><au>Ghodsypour, S. Hassan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A bi-level multi-follower optimization model for R&D project portfolio: an application to a pharmaceutical holding company</atitle><jtitle>Annals of operations research</jtitle><stitle>Ann Oper Res</stitle><addtitle>Ann Oper Res</addtitle><date>2023-04-01</date><risdate>2023</risdate><volume>323</volume><issue>1-2</issue><spage>331</spage><epage>360</epage><pages>331-360</pages><issn>0254-5330</issn><eissn>1572-9338</eissn><abstract>The need for a study of project portfolio optimization in pharmaceutical R&D has become all the more urgent with the outbreak of COVID-19. This study examines a new model for optimizing R&D project portfolios under a decentralized decision-making structure in a pharmaceutical holding company. Specifically, two levels of decision makers hierarchically decide on budget allocation and project portfolio selection-scheduling to maximize their profit, and we formulate the problem as a bi-level multi-follower mixed-integer optimization model. At the upper level, the investment company has complete knowledge of the subsidiaries' response, acts first, and decides on the best budget allocation. At the lower level, each subsidiary responds to the allocated budget and decides on its portfolio scheduling. Since the lower level represents several mixed-integer programming problems, solving the resulting bi-level model is challenging. Therefore, we propose an efficient hybrid solution approach based on parametric optimization and convert the bi-level model into a single-level mixed-integer model. To validate it, we solve a case and discuss the optimal strategy of each actor. 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subjects | Analysis Budgets Business and Management Combinatorics Company structure Computer Science Decision making Industrial project management Industrial research Integer programming Investments Iran Life Sciences Management Mathematical optimization Mixed integer Operations Research Operations Research/Decision Theory Optimization Optimization models Pharmaceutical sciences Pharmaceuticals Project management R&D Research & development Scheduling Special: OR in Medicine/Ed. Lee Subsidiaries Theory of Computation |
title | A bi-level multi-follower optimization model for R&D project portfolio: an application to a pharmaceutical holding company |
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