IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v203y2010i1p205-215.html
   My bibliography  Save this article

Modeling methods and a branch and cut algorithm for pharmaceutical clinical trial planning using stochastic programming

Author

Listed:
  • Colvin, Matthew
  • Maravelias, Christos T.

Abstract

We discuss methods for the solution of a multi-stage stochastic programming formulation for the resource-constrained scheduling of clinical trials in the pharmaceutical research and development pipeline. First, we present a number of theoretical properties to reduce the size and improve the tightness of the formulation, focusing primarily on non-anticipativity constraints. Second, we develop a novel branch and cut algorithm where necessary non-anticipativity constraints that are unlikely to be active are removed from the initial formulation and only added if they are violated within the search tree. We improve the performance of our algorithm by combining different node selection strategies and exploring different approaches to constraint violation checking.

Suggested Citation

  • Colvin, Matthew & Maravelias, Christos T., 2010. "Modeling methods and a branch and cut algorithm for pharmaceutical clinical trial planning using stochastic programming," European Journal of Operational Research, Elsevier, vol. 203(1), pages 205-215, May.
    • Handle: RePEc:eee:ejores:v:203:y:2010:i:1:p:205-215
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00524-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tore Jonsbråten & Roger Wets & David Woodruff, 1998. "A class of stochastic programs withdecision dependent random elements," Annals of Operations Research, Springer, vol. 82(0), pages 83-106, August.
    2. Herroelen, Willy & Leus, Roel, 2005. "Project scheduling under uncertainty: Survey and research potentials," European Journal of Operational Research, Elsevier, vol. 165(2), pages 289-306, September.
    3. Kjetil Haugen & Stein Wallace, 2006. "Stochastic programming: Potential hazards when random variables reflect market interaction," Annals of Operations Research, Springer, vol. 142(1), pages 119-127, February.
    4. Russell W. Bent & Pascal Van Hentenryck, 2004. "Scenario-Based Planning for Partially Dynamic Vehicle Routing with Stochastic Customers," Operations Research, INFORMS, vol. 52(6), pages 977-987, December.
    5. DiMasi, Joseph A. & Hansen, Ronald W. & Grabowski, Henry G., 2003. "The price of innovation: new estimates of drug development costs," Journal of Health Economics, Elsevier, vol. 22(2), pages 151-185, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maier, Sebastian & Pflug, Georg C. & Polak, John W., 2020. "Valuing portfolios of interdependent real options under exogenous and endogenous uncertainties," European Journal of Operational Research, Elsevier, vol. 285(1), pages 133-147.
    2. Peter Buchholz & Dimitri Scheftelowitsch, 2019. "Computation of weighted sums of rewards for concurrent MDPs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(1), pages 1-42, February.
    3. Tahir Ekin & Nicholas G. Polson & Refik Soyer, 2017. "Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(8), pages 613-627, December.
    4. Abdoli, B. & Hooshmand, F. & MirHassani, S.A., 2023. "A novel stochastic programming model under endogenous uncertainty for the CCS-EOR planning problem," Applied Energy, Elsevier, vol. 338(C).
    5. Feng, Wei & Feng, Yiping & Zhang, Qi, 2021. "Multistage robust mixed-integer optimization under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 294(2), pages 460-475.
    6. F. Hooshmand & S. A. MirHassani, 2018. "Reduction of nonanticipativity constraints in multistage stochastic programming problems with endogenous and exogenous uncertainty," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 87(1), pages 1-18, February.
    7. Fleischhacker, Adam J. & Zhao, Yao, 2011. "Planning for demand failure: A dynamic lot size model for clinical trial supply chains," European Journal of Operational Research, Elsevier, vol. 211(3), pages 496-506, June.
    8. Sha, Yue & Zhang, Junlong & Cao, Hui, 2021. "Multistage stochastic programming approach for joint optimization of job scheduling and material ordering under endogenous uncertainties," European Journal of Operational Research, Elsevier, vol. 290(3), pages 886-900.
    9. Giovanni Pantuso, 2021. "A node formulation for multistage stochastic programs with endogenous uncertainty," Computational Management Science, Springer, vol. 18(3), pages 325-354, July.
    10. Lars Hellemo & Paul I. Barton & Asgeir Tomasgard, 2018. "Decision-dependent probabilities in stochastic programs with recourse," Computational Management Science, Springer, vol. 15(3), pages 369-395, October.
    11. Suhan Wu & Min Luo & Jingxia Zhang & Daoheng Zhang & Lianmin Zhang, 2022. "Pharmaceutical Supply Chain in China: Pricing and Production Decisions with Price-Sensitive and Uncertain Demand," Sustainability, MDPI, vol. 14(13), pages 1-28, June.
    12. Kavitha G. Menon & Ricardo Fukasawa & Luis A. Ricardez-Sandoval, 2021. "A novel stochastic programming approach for scheduling of batch processes with decision dependent time of uncertainty realization," Annals of Operations Research, Springer, vol. 305(1), pages 163-190, October.
    13. Salo, Ahti & Andelmin, Juho & Oliveira, Fabricio, 2022. "Decision programming for mixed-integer multi-stage optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 299(2), pages 550-565.
    14. Colvin, Matthew & Maravelias, Christos T., 2011. "R&D pipeline management: Task interdependencies and risk management," European Journal of Operational Research, Elsevier, vol. 215(3), pages 616-628, December.
    15. Solak, Senay & Clarke, John-Paul B. & Johnson, Ellis L. & Barnes, Earl R., 2010. "Optimization of R&D project portfolios under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 207(1), pages 420-433, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nesbitt, Peter & Blake, Lewis R. & Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo K. & Newman, Alexandra & Brickey, Andrea, 2021. "Underground mine scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 294(1), pages 340-352.
    2. Wiesemann, Wolfram & Kuhn, Daniel & Rustem, Berç, 2010. "Maximizing the net present value of a project under uncertainty," European Journal of Operational Research, Elsevier, vol. 202(2), pages 356-367, April.
    3. Emad Sadoon & Uday Venkatadri & Alireza Ghasemi, 2023. "A Conceptual Framework for Logistics Management and Project Planning in the Clinical Trials Industry," Logistics, MDPI, vol. 7(4), pages 1-42, November.
    4. Colvin, Matthew & Maravelias, Christos T., 2011. "R&D pipeline management: Task interdependencies and risk management," European Journal of Operational Research, Elsevier, vol. 215(3), pages 616-628, December.
    5. Wolfram Wiesemann & Daniel Kuhn & Berç Rustem, 2012. "Multi-resource allocation in stochastic project scheduling," Annals of Operations Research, Springer, vol. 193(1), pages 193-220, March.
    6. Kaut, Michal & Vaagen, Hajnalka & Wallace, Stein W., 2021. "The combined impact of stochastic and correlated activity durations and design uncertainty on project plans," International Journal of Production Economics, Elsevier, vol. 233(C).
    7. Holger Patzelt & Dean A. Shepherd, 2009. "Strategic Entrepreneurship at Universities: Academic Entrepreneurs’ Assessment of Policy Programs," Entrepreneurship Theory and Practice, , vol. 33(1), pages 319-340, January.
    8. Patzelt, Holger & zu Knyphausen-Aufseß, Dodo & Fischer, Heiko T., 2009. "Upper echelons and portfolio strategies of venture capital firms," Journal of Business Venturing, Elsevier, vol. 24(6), pages 558-572, November.
    9. Xiong, Jian & Leus, Roel & Yang, Zhenyu & Abbass, Hussein A., 2016. "Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project," European Journal of Operational Research, Elsevier, vol. 251(2), pages 662-675.
    10. Dosis, Anastasios & Muthoo, Abhinay, 2019. "Experimentation in Dynamic R&D Competition," CRETA Online Discussion Paper Series 52, Centre for Research in Economic Theory and its Applications CRETA.
    11. Servranckx, Tom & Vanhoucke, Mario, 2019. "Strategies for project scheduling with alternative subgraphs under uncertainty: similar and dissimilar sets of schedules," European Journal of Operational Research, Elsevier, vol. 279(1), pages 38-53.
    12. Almeder, Christian & Hartl, Richard F., 2013. "A metaheuristic optimization approach for a real-world stochastic flexible flow shop problem with limited buffer," International Journal of Production Economics, Elsevier, vol. 145(1), pages 88-95.
    13. Tomas J. Philipson & Eric Sun, 2008. "Is the Food And Drug Administration Safe And Effective?," Journal of Economic Perspectives, American Economic Association, vol. 22(1), pages 85-102, Winter.
    14. Ming Liu & Sumner LaCroix, 2011. "The Impact of Stronger Property Rights in Pharmaceuticals on Innovation in Developed and Developing Countries," Working Papers 201116, University of Hawaii at Manoa, Department of Economics.
    15. Morteza Davari & Erik Demeulemeester, 2019. "The proactive and reactive resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 22(2), pages 211-237, April.
    16. Edouard Debonneuil & Anne Eyraud-Loisel & Frédéric Planchet, 2018. "Can Pension Funds Partially Manage Longevity Risk by Investing in a Longevity Megafund?," Risks, MDPI, vol. 6(3), pages 1-27, July.
    17. Eric Budish & Benjamin Roin & Heidi Williams, 2013. "Do fixed patent terms distort innovation? Evidence from cancer clinical trials," Discussion Papers 13-001, Stanford Institute for Economic Policy Research.
    18. Waters, James, 2014. "Introduction of innovations during the 2007-8 financial crisis: US companies compared with universities," MPRA Paper 59016, University Library of Munich, Germany.
    19. Wolfgang Hein & Lars Kohlmorgen, 2005. "Global Health Governance: Conflicts on Global Social Rights," HEW 0509001, University Library of Munich, Germany.
    20. Marlin W. Ulmer & Alan Erera & Martin Savelsbergh, 2022. "Dynamic service area sizing in urban delivery," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 763-793, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:203:y:2010:i:1:p:205-215. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.