Abstract
In this study, we address a public R&D project portfolio selection problem with project cancellations. For several reasons, a funded R&D project may be halted before finishing the planned research. When a project is canceled, most of its budget is usually unused and also some of the spendings can return to the funding organization. In the call-based R&D programs, usually project selection decisions are made in one go, and, in the current call, it is not possible to award new projects with the unused budget. Decision-makers (DMs) of funding organizations can benefit from considering possible project cancellation situations to improve the budget utilization. We consider two cases. In the first case, we assume that cancellation probability of a project cannot be assessed but the DM can estimate the number of projects that will be canceled. In the second case, we assume that for each project, a cancellation probability can be assessed. For the first problem, we develop a mixed-integer linear programming formulation and a dynamic programming algorithm. For the second problem, we develop a chance-constrained stochastic programming formulation that can be solved as a mixed-integer second-order cone program. Our computational results show that practical-size problems can be solved by the proposed solution approaches.
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References
Baurer H (1996) Probability Theory. De Gruyter Studies in Mathematics, vol. 23. Walter de Gruyter, Transl. by Burckel, Robert B., Berlin
Beaujon GJ, Marin SP, McDonald GC (2001) Balancing and optimizing a portfolio of R&D projects. Naval Res Logist 48(1):18–40
Bertsimas D, Sim M (2004) The price of robustness. Oper Res 52(1):35–53
Duzgun R, Thiele A (2010) Robust optimization with multiple ranges: theory and application to R&D project selection. Technical Report, Lehigh University, Bethlehem
Eilat H, Golany B, Shtub A (2006) Constructing and evaluating balanced portfolios of R&D projects with interactions: a DEA based methodology. Eur J Oper Res 172:1018–1039
Eser A (2014) Ar-ge ve yenilik ekosistemimiz ve mevcut kamu ar-ge destekleri. Kalkinmada Anahtar Verimlilik 301:15–17. https://anahtar.sanayi.gov.tr/tr/news/ar-ge-ve-yenilik-ekosistemimiz-ve-mevcut-kamu-ar-ge-destekleri/664
Gerchak Y, Kilgour DM (1999) Optimal parallel funding of research and development projects. IIE Trans 31(2):145–152
Gerchak Y, Parlar M (1999) Allocating resources to research and development projects in a competitive environment. IIE Trans 31(9):827–834
Gupte A, Ahmed S, Cheon MS, Dey S (2013) Solving mixed integer bilinear problems using MILP formulations. SIAM J Optim 23(2):721–744
Heidenberger K, Stummer C (1999) Research and development project selection and resource allocation: a review of quantitative modelling approaches. Int J Manag Rev 1(2):197–224
Henriksen AD, Traynor AJ (1999) A practical R&D project-selection scoring tool. IEEE Trans Eng Manag 46(2):158–170
Hong Y (2013) On computing the distribution function for the Poisson binomial distribution. Comput Stat Data Anal 59:41–51
Klotz E, Newman AM (2013) Practical guidelines for solving difficult mixed integer linear programs. Surveys Oper Res Manag Sci 18(1–2):18–32
Kroll H, Stahlecker T (2012) Global review of competitive R&D funding—a project commissioned by the World Bank. Synthesis Report
Litvinchev IS, Lopez F, Alvarez A, Fernandez E (2010) Large-scale public R&D portfolio selection by maximizing a biobjective impact measure. IEEE Trans Syst Man Cybern Part A Syst Hum 40(3):572–582
McCormick GP (1976) Computability of global solutions to factorable nonconvex programs. 1. Convex underestimating problems. Math Program 10(2):147–175
Monaci M, Pferschy U, Serafini P (2013) Exact solution of the robust knapsack problem. Comput Oper Res 40(11):2625–2631
Nelson RR (2004) The challenge of building an effective innovation system for catch-up. Oxford Dev Studies 32(3):365–374
NIH (2013) National Institutes of Health, Grant Policy Statements. grants.nih.gov/grants/policy/policy.htm
NSF (2005) National Science Foundation, Grant Policy Manual
Ringuest JL, Graves SB, Case RH (2004) Mean-gini analysis in R&D portfolio selection. Eur J Oper Res 154(1):157–169
Shapiro A, Dentcheva D, Ruszczynski A (2009) Lectures on stochastic programming: modeling and theory, 1st edn. SIAM, Philadelphia
Solak S, Clarke JPB, Johnson EL, Barnes ER (2010) Optimization of R&D project portfolios under endogenous uncertainty. Eur J Oper Res 207(1):420–433
TÜBİTAK (2012) Activity report. https://www.tubitak.gov.tr/sites/default/files/tubitak_2012_faaliyet_raporu_web.pdf
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The authors thank the two anonymous referees for comments and suggestions that improved the paper.
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Çağlar, M., Gürel, S. Public R&D project portfolio selection problem with cancellations. OR Spectrum 39, 659–687 (2017). https://doi.org/10.1007/s00291-016-0468-5
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DOI: https://doi.org/10.1007/s00291-016-0468-5