Project portfolio selection problems: a review of models, uncertainty approaches, solution techniques, and case studies
Abstract
Project portfolio selection has been the focus of many scholars in the last two decades. The number of studies on the strategic process has significantly increased over the past decade. Despite this increasing trend, previous studies have not been yet critically evaluated. This paper, therefore, aims to presents a comprehensive review of project portfolio selection and optimization studies focusing on the evaluation criteria, selection approach, solution approach, uncertainty modeling, and applications. This study reviews more than 140 papers on project portfolio selection research topic to identify the gaps and to present future trends. The findings show that not only the financial criteria but also social and environmental aspects of project portfolios have been focused by researchers in project portfolio selection in recent years. In addition, meta-heuristics and heuristics approach to finding the solution of mathematical models have been the critical research by scholars. Expert systems, artificial intelligence, and big data science have not been considered in project portfolio selection in the previous studies. In future, researchers can investigate the role of sustainability, resiliency, foreign investment, and exchange rates in project portfolio selection studies, and they can focus on artificial intelligence environments using big data and fuzzy stochastic optimization techniques.
Keyword : project portfolio selection, uncertainty approach, solution approach, selection approach, evaluation criteria, case studies
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Archer, N. P., & Ghasemzadeh, F. (1998). A decision support system for project portfolio selection. International Journal of Technology Management, 16(1-3), 105-114.
Archer, N. P., & Ghasemzadeh, F. (1999). An integrated framework for project portfolio selection. International Journal of Project Management, 17(4), 207-216. https://doi.org/10.1016/S0263-7863(98)00032-5
Aritua, B., Smith, N. J., & Bower, D. (2009). Construction client multi-projects–A complex adaptive systems perspective. International Journal of Project Management, 27(1), 72-79. https://doi.org/10.1016/j.ijproman.2008.02.005
Atanassov, K. T. (1994). New operations defined over the intuitionistic fuzzy sets. Fuzzy Sets and Systems, 61(2), 137-142. https://doi.org/10.1016/0165-0114(94)90229-1
Balderas, F., Fernandez, E., Gomez, C., & Cruz-Reyes, L. (2017). TOPSIS-grey method applied to project portfolio problem. In Nature-inspired design of hybrid intelligent systems (pp. 767-774). Springer International Publishing. https://doi.org/10.1007/978-3-319-47054-2_51
Balderas, F., Fernandez, E., Gomez-Santillan, C., Cruz-Reyes, L., Rangel-Valdez, N., & Morales-Rodríguez, M. L. (2018). A grey mathematics approach for evolutionary multi-objective metaheuristic of project portfolio selection. In Fuzzy logic augmentation of neural and optimization algorithms: theoretical aspects and real applications (pp. 379-388). Cham: Springer. https://doi.org/10.1007/978-3-319-71008-2_27
Bas, E. (2012). Surrogate relaxation of a fuzzy multidimensional 0–1 knapsack model by surrogate constraint normalization rules and a methodology for multi-attribute project portfolio selection. Engineering Applications of Artificial Intelligence, 25(5), 958-970. https://doi.org/10.1016/j.engappai.2011.09.015
Better, M., & Glover, F. (2006). Selecting project portfolios by optimizing simulations. The Engineering Economist, 51(2), 81-97. https://doi.org/10.1080/00137910600695593
Bhattacharyya, R. (2015). A grey theory based multiple attribute approach for R&D project portfolio selection. Fuzzy Information and Engineering, 7(2), 211-225. https://doi.org/10.1016/j.fiae.2015.05.006
Bhattacharyya, R., Chatterjee, A., & Kar, S. (2010). Uncertainty theory based novel multi-objective optimization technique using embedding theorem with application to R & D project portfolio selection. Applied Mathematics, 1(03), 189-199. https://doi.org/10.4236/am.2010.13023
Brauers, W. K. M., & Zavadskas, E. K. (2010). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5-24. https://doi/abs/10.3846/tede.2010.01
Çağlar, M., & Gürel, S. (2017). Public R&D project portfolio selection problem with cancellations. OR Spectrum, 39(3), 659-687. https://doi.org/10.1007/s00291-016-0468-5
Carazo, A. F. (2015). Multi-criteria project portfolio selection. In Handbook on project management and scheduling (Vol. 2, pp. 709-728). Springer International Publishing. https://doi.org/10.1007/978-3-319-05915-0_3
Carazo, A. F., Gómez, T., Molina, J., Hernández-Díaz, A. G., Guerrero, F. M., & Caballero, R. (2010). Solving a comprehensive model for multiobjective project portfolio selection. Computers & Operations Research, 37(4), 630-639. https://doi.org/10.1016/j.cor.2009.06.012
Carlsson, C., Fullér, R., Heikkilä, M., & Majlender, P. (2007). A fuzzy approach to R&D project portfolio selection. International Journal of Approximate Reasoning, 44(2), 93-105. https://doi.org/10.1016/j.ijar.2006.07.003
Chu, P. Y. V., Hsu, Y. L., & Fehling, M. (1996). A decision support system for project portfolio selection. Computers in Industry, 32(2), 141-149. https://doi.org/10.1016/S0166-3615(96)00067-X
Conka, T., Vayvay, O., & Sennaroglu, B. (2008). A combined decision model for R&D project portfolio selection. International Journal of Business Innovation and Research, 2(2), 190-202. https://doi.org/10.1504/IJBIR.2008.016652
Cruz-Reyes, L., Medina, C., & López, F. (2013). An interactive decision support system framework for social project portfolio selection. In Recent advances on hybrid intelligent systems (pp. 377-391). Berlin, Heidelberg: Springer. Retrieved from https://link.springer.com/chapter/10.1007/978-3-642-33021-6_30
Cruz-Reyes, L., Trejo, C. M., Irrarragorri, F. L., & Santillán, C. G. G. (2014). A decision support system framework for public project portfolio selection with argumentation theory. In Recent advances on hybrid approaches for designing intelligent systems (pp. 467-479). Springer International Publishing. Retrieved from https://link.springer.com/chapter/10.1007%2F978-3-319-05170-3_32
Davoudabadi, R., Mousavi, S. M., Šaparauskas, J., & Gitinavard, H. (2019). Solving construction project selection problem by a new uncertain weighting and ranking based on compromise solution with linear assignment approach. Journal of Civil Engineering and Management, 25(3), 241-251. https://doi.org/10.3846/jcem.2019.8656
Debnath, A., Roy, J., Kar, S., Zavadskas, E. K., & Antucheviciene, J. (2017). A hybrid MCDM approach for strategic project portfolio selection of agro by-products. Sustainability, 9(8), 1302. https://doi.org/10.3390/su9081302
Dobrovolskienė, N., & Tamošiūnienė, R. (2016). Sustainability-oriented financial resource allocation in a project portfolio through multi-criteria decision-making. Sustainability, 8(5), 485. Retrieved from https://www.mdpi.com/2071-1050/8/5/485
Doerner, K. F., Gutjahr, W. J., Hartl, R. F., Strauss, C., & Stummer, C. (2006). Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection. European Journal of Operational Research, 171(3), 830-841. https://doi.org/10.1016/j.ejor.2004.09.009
Dong, J., & Wan, S. (2019). A new method for solving fuzzy multi-objective linear programming problems. Iranian Journal of Fuzzy Systems, 16(3), 145-159.
Dong, J., Lai, K. K., & Wang, S. (2005). XML-based schemes for business project portfolio selection. In Data mining and knowledge management (pp. 254-262). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-540-30537-8_28
Dorfeshan, Y., Mousavi, S. M., Mohagheghi, V., & Vahdani, B. (2018). Selecting project-critical path by a new interval type-2 fuzzy decision methodology based on MULTIMOORA, MOOSRA and TPOP methods. Computers & Industrial Engineering, 120, 160-178. https://doi.org/10.1016/j.cie.2018.04.015
Ebrahimnejad, S., Mousavi, S. M., Tavakkoli-Moghaddam, R., Hashemi, H., & Vahdani, B. (2012). A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling, 36(9), 4197-4217. https://doi.org/10.1016/j.apm.2011.11.050
Ebrahimnejad, S., Mousavi, S. M., Tavakkoli-Moghaddam, R., & Heydar, M. (2014). Risk ranking in mega projects by fuzzy compromise approach: A comparative analysis. Journal of Intelligent and Fuzzy Systems, 26, 949-959. https://doi.org/10.3233/IFS-130785
Esfahani, H. N., Hossein Sobhiyah, M., & Yousefi, V. R. (2016). Project portfolio selection via harmony search algorithm and modern portfolio theory. Procedia-Social and Behavioral Sciences, 226, 51-58. https://doi.org/10.1016/j.sbspro.2016.06.161
Farshchian, M. M., & Heravi, G. (2018). Probabilistic assessment of cost, time, and revenue in a portfolio of projects using stochastic agent-based simulation. Journal of Construction Engineering and Management, 144(5). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001476
Felberbauer, T., Gutjahr, W. J., & Doerner, K. F. (2018). Stochastic project management: multiple projects with multi-skilled human resources. Journal of Scheduling, 22(3), 271-288. https://doi.org/10.1007/s10951-018-0592-y
Fernandez, E., Lopez, E., Mazcorro, G., Olmedo, R., & Coello, C. A. C. (2013). Application of the non-outranked sorting genetic algorithm to public project portfolio selection. Information Sciences, 228, 131-149. https://doi.org/10.1016/j.ins.2012.11.018
Fouladgar, M. M., Yazdani-Chamzini, A., Yakhchali, S. H., Ghasempourabadi, M. H., & Badri, N. (2011, September). Project portfolio selection using VIKOR technique under fuzzy environment. In 2nd International Conference on Construction and Project Management (pp. 236-240). Retrieved from https://www.academia.edu/download/11495265/46-iccpm2011a10032
Gang, J., Hu, R., Wu, T., Tu, Y., Feng, C., & Li, Y. (2015). R&D project portfolio selection in a bi-level investment environment: a case study from a research institute in China. In Proceedings of the Ninth International Conference on Management Science and Engineering Management (pp. 563-574). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-662-47241-5_48
Ghaeli, M., Vavrik, J., & Nasvadi, G. (2003). Multicriteria project portfolio selection: Case study for intelligent transportation systems. Transportation Research Record: Journal of the Transportation Research Board, 1848(1), 125-131. https://doi.org/10.3141/1848-18
Ghasemzadeh, F., Archer, N., & Iyogun, P. (1999). A zero-one model for project portfolio selection and scheduling. Journal of the Operational Research Society, 50(7), 745-755. https://doi.org/10.1057/palgrave.jors.2600767
Ghassemi, A., & Amalnick, M. (2018). NPD project portfolio selection using reinvestment strategy in competitive environment. International Journal of Industrial Engineering Computations, 9(1), 47-62. https://doi.org/10.5267/j.ijiec.2017.5.001
Ghodoosi, M. R., Maftahi, R., & Yousefi, V. (2016). Proposing a hybrid approach to predict, schedule and select the most robust project portfolio under uncertainty. European Online Journal of Natural and Social Sciences, 5(4), 1099-1110. http://european-science.com/eojnss/article/view/4707
Graves, S. B., Ringuest, J. L., & Medaglia, A. L. (2003). Conditional stochastic dominance in project portfolio selection. In Models & methods for project selection (pp. 77-93). US: Springer. https://doi.org/10.1007/978-1-4615-0280-7_6
Guo, P., Liang, J. J., Zhu, Y. M., & Hu, J. F. (2008, December). R&D project portfolio selection model analysis within project interdependencies context. In 2008 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 994-998), Singapore. IEEE. https://doi.org/10.1109/IEEM.2008.4738019
Gurgur, C. (2009). Optimal project portfolio selection with carryover constraint. Journal of the Operational Research Society, 60(12), 1649-1657. https://doi.org/10.1057/jors.2008.104
Gutjahr, W. J., & Froeschl, K. A. (2013). Project portfolio selection under uncertainty with outsourcing opportunities. Flexible Services and Manufacturing Journal, 25(1-2), 255-281. https://doi.org/10.1007/s10696-011-9107-2
Gutjahr, W. J., & Reiter, P. (2010). Bi-objective project portfolio selection and staff assignment under uncertainty. Optimization, 59(3), 417-445. https://doi.org/10.1080/02331931003700699
Gutjahr, W. J., Katzensteiner, S., Reiter, P., Stummer, C., & Denk, M. (2010). Multi-objective decision analysis for competence-oriented project portfolio selection. European Journal of Operational Research, 205(3), 670-679. https://doi.org/10.1016/j.ejor.2010.01.041
Gutjahr, W. J., Katzensteiner, S., Reiter, P., Stummer, C., & Denk, M. (2008). Competence-driven project portfolio selection, scheduling and staff assignment. Central European Journal of Operations Research, 16(3), 281-306. https://doi.org/10.1007/s10100-008-0057-z
Haghighi, M. H., Mousavi, S. M., Antuchevičienė, J., & Mohagheghi, V. (2019). A new analytical methodology to handle time-cost trade-off problem with considering quality loss cost under interval-valued fuzzy uncertainty. Technological and Economic Development of Economy, 25(2), 277-299. https://doi.org/10.3846/tede.2019.8422
Hall, N. G., Long, D. Z., Qi, J., & Sim, M. (2015). Managing underperformance risk in project portfolio selection. Operations Research, 63(3), 660-675. https://doi.org/10.1287/opre.2015.1382
Hannah, L. A. (2015). Stochastic optimization. International Encyclopedia of the Social & Behavioral Sciences, 2, 473-481. https://doi.org/10.1016/B978-0-08-097086-8.42010-6
Hashemi, H., Mousavi, S. M., & Mojtahedi, S. M. H. (2011). Bootstrap technique for risk analysis with interval numbers in bridge construction projects. Journal of Construction Engineering and Management – ASCE, 137(8), 600-608. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000344
Hashemi, H., Mousavi, S. M., Tavakkoli-Moghaddam, R., & Gholipour, Y. (2013). Compromise ranking approach with bootstrap confidence intervals for risk assessment in port management projects. Journal of Management in Engineering, 29(4), 334-344. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000167
Hassanzadeh, F., Modarres, M., Nemati, H. R., & Amoako-Gyampah, K. (2014a). A robust R&D project portfolio optimization model for pharmaceutical contract research organizations. International Journal of Production Economics, 158, 18-27. https://doi.org/10.1016/j.ijpe.2014.07.001
Hassanzadeh, F., Nemati, H., & Sun, M. (2014b). Robust optimization for interactive multiobjective programming with imprecise information applied to R&D project portfolio selection. European Journal of Operational Research, 238(1), 41-53. https://doi.org/10.1016/j.ejor.2014.03.023
Hu, G., Wang, L., Fetch, S., & Bidanda, B. (2008). A multi-objective model for project portfolio selection to implement lean and Six Sigma concepts. International Journal of Production Research, 46(23), 6611-6625. https://doi.org/10.1080/00207540802230363
Hu, Q. J., & Szmerekovsky, J. (2016). Project portfolio selection: a newsvendor approach. Decision Sciences, 48(1), 176-199. https://doi.org/10.1111/deci.12214
Huang, X., & Zhao, T. (2014). Project selection and scheduling with uncertain net income and investment cost. Applied Mathematics and Computation, 247, 61-71. https://doi.org/10.1016/j.amc.2014.08.082
Huang, X., & Zhao, T. (2016). Project selection and adjustment based on uncertain measure. Information Sciences, 352, 1-14. https://doi.org/10.1016/j.ins.2016.02.050
Huang, X., Zhao, T., & Kudratova, S. (2016). Uncertain mean-variance and mean-semivariance models for optimal project selection and scheduling. Knowledge-Based Systems, 93, 1-11. https://doi.org/10.1016/j.knosys.2015.10.030
Humel, J. M., Oliveira, M. D., e Costa, C. A. B., & IJzerman, M. J. (2017). Supporting the project portfolio selection decision of research and development investments by means of multi-criteria resource allocation modelling. In Multi-criteria decision analysis to support healthcare decisions (pp. 89-103). Cham: Springer. https://doi.org/10.1007/978-3-319-47540-0_6
Hutchins, M. J., & Sutherland, J. W. (2008). An exploration of measures of social sustainability and their application to supply chain decisions. Journal of Cleaner Production, 16(15), 1688-1698. https://doi.org/10.1016/j.jclepro.2008.06.001
Jadda, S., & Idrissi, M. A. J. (2015, October). Strategic alignment and information system project portfolio optimization model. In 2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA) (pp. 1-8). IEEE. https://doi.org/10.1109/SITA.2015.7358385
Jafarzadeh, M., Tareghian, H. R., Rahbarnia, F., & Ghanbari, R. (2015). Optimal selection of project portfolios using reinvestment strategy within a flexible time horizon. European Journal of Operational Research, 243(2), 658-664. https://doi.org/10.1016/j.ejor.2014.12.013
Jeng, D. J. F., & Huang, K. H. (2015). Strategic project portfolio selection for national research institutes. Journal of Business Research, 68(11), 2305-2311. https://doi.org/10.1016/j.jbusres.2015.06.016
Jiang, J. (2018, June 9-13). System portfolio selection under hesitant fuzzy information. In Y. Chen, G. Kersten, R. Vetschera, & H. Xu (Eds.), Group Decision and Negotiation in an Uncertain World: 18th International Conference, GDN 2018 (Vol. 315, p. 33-34), Nanjing, China. Cham: Springer. https://doi.org/10.1007/978-3-319-92874-6_3
Jingmei, W., & Peng, G. (2015, August). The robustness risk and selection optimization of R&D project portfolio under uncertainty. In 2015 IEEE International Conference on Grey Systems and Intelligent Services (pp. 622-627). IEEE. https://doi.org/10.1109/GSIS.2015.7301817
Julong, D. (1989). Introduction to grey system theory. The Journal of Grey System, 1(1), 1-24.
Kaiser, M. G., El Arbi, F., & Ahlemann, F. (2015). Successful project portfolio management beyond project selection techniques: Understanding the role of structural alignment. International Journal of Project Management, 33(1), 126-139. https://doi.org/10.1016/j.ijproman.2014.03.002
Kettunen, J., & Salo, A. (2017). Estimation of downside risks in project portfolio selection. Production and Operations Management, 26(10), 1839-1853. https://doi.org/doi:10.1111/poms.12727
Khalili-Damghani, K., & Sadi-Nezhad, S. (2013a). Strategic framework for sustainable project portfolio selection and evaluation. International Journal of Sustainable Strategic Management, 4(1), 66-82. https://doi.org/10.1504/IJSSM.2013.056391
Khalili‐Damghani, K., & Tavana, M. (2014). A comprehensive framework for sustainable project portfolio selection based on structural equation modeling. Project Management Journal, 45(2), 83-97. https://doi.org/10.1002/pmj.21404
Khalili-Damghani, K., Sadi-Nezhad, S., Lotfi, F. H., & Tavana, M. (2013). A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection. Information Sciences, 220, 442-462. https://doi.org/10.1016/j.ins.2012.07.024
Khalili-Damghani, K., & Sadi-Nezhad, S. (2013b). A hybrid fuzzy multiple criteria group decision making approach for sustainable project selection. Applied Soft Computing, 13(1), 339-352. https://doi.org/10.1016/j.asoc.2012.07.030
Killen, C. P., & Hunt, R. A. (2013). Robust project portfolio management: capability evolution and maturity. International Journal of Managing Projects in Business, 6(1), 131-151. https://doi.org/10.1108/17538371311291062
Koppinen, T., & Rosqvist, T. (2010). Dynamic project portfolio selection in infrastructure sector. In Definitions, concepts and scope of engineering asset management (pp. 311-326). London: Springer. https://doi.org/10.1007/978-1-84996-178-3_16
Li, F., Cao, R., Li, S., Guo, C., & Zhao, X. (2012, July). Parameterized model and approach for constrained project portfolio optimization. In 2012 IEEE International Conference on Service Operations and Logistics, and Informatics (pp. 462-467). IEEE. https://doi.org/10.1109/SOLI.2012.6273581
Li, L., Li, J., Qin, Q., & Cheng, S. (2014). Fuzzy chance-constrained project portfolio selection model based on credibility theory. In Foundations of intelligent systems (pp. 731-743). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-54924-3_69
Li, X., Fang, S. C., Guo, X., Deng, Z., & Qi, J. (2016). An extended model for project portfolio selection with project divisibility and interdependency. Journal of Systems Science and Systems Engineering, 25(1), 119-138. https://doi.org/10.1007/s11518-015-5281-1
Li, X., Fang, S. C., Tian, Y., & Guo, X. (2015). Expanded model of the project portfolio selection problem with divisibility, time profile factors and cardinality constraints. Journal of the Operational Research Society, 66(7), 1132-1139. https://doi.org/10.1057/jors.2014.75
Li, X., Wang, Y., Yan, Q., & Zhao, X. (2018). Uncertain mean-variance model for dynamic project portfolio selection problem with divisibility. Fuzzy Optimization and Decision Making, 18(1), 37-56. https://doi.org/10.1007/s10700-018-9283-6
Li, X., Zhong, Z., Zhang, Y., & Wang, Y. (2017). Uncertain mean-variance model for project portfolio selection problem with divisibility. Journal of Intelligent & Fuzzy Systems, 32(6), 4513-4522. https://doi.org/10.3233/JIFS-169215
Lifshits, A. A., & Avdoshin, S. M. (2016). Algorithms for project portfolio selection based on fuzzy multi-objective model. In Emerging trends in information systems (pp. 65-77). Springer International Publishing. https://doi.org/10.1007/978-3-319-23929-3_6
Liu, B. (2007). Uncertainty theory. In Uncertainty theory (pp. 205-234). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-540-73165-8_5
Liu, Y., & Liu, Y. K. (2017). Distributionally robust fuzzy project portfolio optimization problem with interactive returns. Applied Soft Computing, 56, 655-668. https://doi.org/10.1016/j.asoc.2016.09.022
Lukovac, V., Pamučar, D., Popović, M., & Đorović, B. (2017). Portfolio model for analyzing human resources: An approach based on neuro-fuzzy modeling and the simulated annealing algorithm. Expert Systems with Applications, 90, 318-331. https://doi.org/10.1016/j.eswa.2017.08.034
Martínez-Vega, D. A., Cruz-Reyes, L., Gomez-Santillan, C., Rangel-Valdez, N., Rivera, G., & Santiago, A. (2018). Modeling and project portfolio selection problem enriched with dynamic allocation of resources. In Fuzzy logic augmentation of neural and optimization algorithms: theoretical aspects and real applications (pp. 365-378). Cham: Springer. https://doi.org/10.1007/978-3-319-71008-2_26
Martins, C. L., López, H. M. L., de Almeida, A. T., Almeida, J. A., & Bortoluzzi, M. B. D. O. (2017). An MCDM project portfolio web-based DSS for sustainable strategic decision making in an electricity company. Industrial Management & Data Systems, 117(7), 1362-1375. https://doi.org/10.1108/IMDS-09-2016-0412
Mavrotas, G., & Pechak, O. (2013a). Combining mathematical programming and Monte Carlo simulation to deal with uncertainty in energy project portfolio selection. In Assessment and simulation tools for sustainable energy systems (pp. 333-356). London: Springer. https://doi.org/10.1007/978-1-4471-5143-2_16
Mavrotas, G., & Pechak, O. (2013b). The trichotomic approach for dealing with uncertainty in project portfolio selection: combining MCDA, mathematical programming and Monte Carlo simulation. International Journal of Multicriteria Decision Making, 3(1), 79-96. https://doi.org/10.1504/IJMCDM.2013.052474
Mendel, J. M., John, R. I., & Liu, F. (2006). Interval type-2 fuzzy logic systems made simple. IEEE Transactions on Fuzzy Systems, 14(6), 808-821. https://doi.org/10.1109/TFUZZ.2006.879986
Mira, C., Feijão, P., Souza, M. A., Moura, A., Meidanis, J., Lima, G., Bossolan, R. P., & Freitas, Ì. T. (2013, July). A project portfolio selection decision support system. In 2013 10th International Conference on Service Systems and Service Management (pp. 725-730). IEEE. https://doi.org/10.1109/ICSSSM.2013.6602536
Mira, C., Feijão, P., Souza, M. A., Moura, A., Meidanis, J., Lima, G., Schmitz, R., Bossolan, R. P., & Freitas, I. T. (2012, December). A GRASP-based heuristic for the project portfolio selection problem. In 2012 IEEE 15th International Conference on Computational Science and Engineering (pp. 36-41). https://doi.org/10.1109/ICCSE.2012.102
Mohagheghi, V., & Mousavi, S. M. (2019). A new framework for high-technology project evaluation and project portfolio selection based on Pythagorean fuzzy WASPAS, MOORA and mathematical modeling. Iranian Journal of Fuzzy Systems, 16(6), 89-106. https://doi.org/10.22111/ijfs.2019.5022
Mohagheghi, V., Mousavi, S. M., & Siadat, A. (2015a). A new approach in considering vagueness and lack of knowledge for selecting sustainable portfolio of production projects. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 1732-1736). https://doi.org/10.1109/IEEM.2015.7385944
Mohagheghi, V., Mousavi, S. M., & Vahdani, B. (2015b). A new optimization model for project portfolio selection under interval-valued fuzzy environment. Arabian Journal for Science and Engineering, 40(11), 3351-3361. https://doi.org/10.1007/s13369-015-1779-6
Mohagheghi, V., Mousavi, S. M., & Vahdani, B. (2016). A new multi-objective optimization approach for sustainable project portfolio selection: a realworld application under interval-valued fuzzy environment. Iranian Journal of Fuzzy Systems, 13(6), 41-68. https://doi.org/10.22111/ijfs.2016.2821
Mohagheghi, V., Mousavi, S. M., Aghamohagheghi, M., & Vahdani, B. (2017a). A new approach of multi-criteria analysis for the evaluation and selection of sustainable transport investment projects under uncertainty: A case study. International Journal of Computational Intelligence Systems, 10, 605-626. https://doi.org/10.2991/ijcis.2017.10.1.41
Mohagheghi, V., Mousavi, S. M., Vahdani, B., & Shahriari, M. R. (2017b). R&D project evaluation and project portfolio selection by a new interval type-2 fuzzy optimization approach. Neural Computing and Applications, 28(12), 3869-3888. https://doi.org/10.1007/s00521-016-2262-3
Mohagheghi, V., Mousavi, S. M., Vahdani, B., & Siadat, A. (2017c). A mathematical modeling approach for high and new technology-project portfolio selection under uncertain environments. Journal of Intelligent and Fuzzy Systems, 32, 4069-4079. https://doi.org/10.3233/JIFS-152510
Mousavi, S. M., Jolai, F., & Tavakkoli-Moghaddam, R. (2013). A fuzzy stochastic multi-attribute group decision-making approach for selection problems. Group Decision and Negotiation, 22(2), 207-233. https://doi.org/10.1007/s10726-011-9259-1
Mousavi, S. M., Tavakkoli-Moghaddam, R., Azaron, A., Mojtahedi, S. M. H., & Hashemi, H. (2011a). Risk assessment for highway projects using jackknife technique. Expert Systems with Applications, 38, 5514-5524. https://doi.org/10.1016/j.eswa.2010.10.085
Mousavi, S. M., Tavakkoli-Moghaddam, R., Hashemi, H., & Mojtahedi, S. M. H. (2011b). A novel approach based on non-parametric resampling with the interval analysis for large engineering project risks. Safety Science, 49, 1340-1348. https://doi.org/10.1016/j.ssci.2011.05.004
Mousavi, S. M., Vahdani, B., Hashemi, H., & Ebrahimnejad, S. (2015). An artificial intelligence model-based locally linear neuro-fuzzy for construction project selection. Journal of Multiple-Valued Logic & Soft Computing, 25(6), 589-604. Retrieved from https://www.oldcitypublishing.com/journals/mvlsc-home/mvlsc-issue-contents/mvlsc-volume-25-number-6-2015/
Naderi, B. (2013). The project portfolio selection and scheduling problem: mathematical model and algorithms. Journal of Optimization in Industrial Engineering, 6(13), 65-72.
Nikkhahnasab, M., & Najafi, A. A. (2013). Project portfolio selection with the maximization of net present value. Journal of Optimization in Industrial Engineering, 6(12), 85-92.
Nowak, M. (2013). Project portfolio selection using interactive approach. Procedia Engineering, 57, 814-822. https://doi.org/10.1016/j.proeng.2013.04.103
Olsson, R. (2008). Risk management in a multi-project environment: An approach to manage portfolio risks. International Journal of Quality & Reliability Management, 25(1), 60-71. https://doi.org/10.1108/02656710810843586
Olundh, G., & Ritzen, S. (2004, October). Making an ecodesign choice in project portfolio selection. In IEEE 2004 Engineering Management Conference (Vol. 3, pp. 913-917).
Panadero, J., Doering, J., Kizys, R., Juan, A. A., & Fito, A. (2018). A variable neighborhood search sim-heuristic for project portfolio selection under uncertainty. Journal of Heuristics, 1-23. https://doi.org/10.1007/s10732-018-9367-z
Perez, F., & Gomez, T. (2016). Multiobjective project portfolio selection with fuzzy constraints. Annals of Operations Research, 245(1-2), 7-29. https://doi.org/10.1007/s10479-014-1556-z
Pérez, F., Gómez, T., Caballero, R., & Liern, V. (2018). Project portfolio selection and planning with fuzzy constraints. Technological Forecasting and Social Change, 131, 117-129. https://doi.org/10.1016/j.techfore.2017.07.012
Project Management Institute. (2008). The standard for portfolio management (2nd ed.). Project Management Institute, Newtown Square, PA.
Qin, Q., Li, J., & Li, L. (2014, May). A fuzzy two-stage project portfolio selection model addressing financial and non-financial factors. In The 26th Chinese Control and Decision Conference (2014 CCDC) (pp. 1349-1353). IEEE. https://doi.org/10.1109/CCDC.2014.6852376
Rabbani, M., Najjarbashi, A., & Joudi, M. (2013). A new multi-objective model for R&D project portfolio selection considering potential repetitive projects and sanction impacts. International Journal of Strategic Decision Sciences (IJSDS), 4(4), 41-54. https://doi.org/10.4018/ijsds.2013100103
Riddell, S., & Wallace, W. A. (2007). The use of fuzzy logic and expert judgment in the R&D project portfolio selection process. In PICMET ’07 − 2007 Portland International Center for Management of Engineering and Technology (pp. 1228-1238). IEEE. https://doi.org/10.1109/PICMET.2007.4349446
Riddell, S., & Wallace, W. A. (2011). The use of fuzzy logic and expert judgment in the R&D project portfolio selection process. International Journal of Technology Management, 53(2-4), 238-256. https://doi.org/10.1504/IJTM.2011.038592
Rivera, G., Gómez, C. G., Fernández, E. R., Cruz, L., Castillo, O., & Bastiani, S. S. (2013). Handling of synergy into an algorithm for project portfolio selection. In Recent Advances on Hybrid Intelligent Systems (pp. 417-430). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-33021-6_33
Roland, J., Figueira, J. R., & De Smet, Y. (2016). Finding compromise solutions in project portfolio selection with multiple experts by inverse optimization. Computers & Operations Research, 66, 12-19. https://doi.org/10.1016/j.cor.2015.07.006
Schaeffer, S. E., & Cruz-Reyes, L. (2016). Static R&D project portfolio selection in public organizations. Decision Support Systems, 84, 53-63. https://doi.org/10.1016/j.dss.2016.01.006
Schniederjans, M. J., & Santhanam, R. (1993). A multi-objective constrained resource information system project selection method. European Journal of Operational Research, 70(2), 244-253. https://doi.org/10.1016/0377-2217(93)90042-L
Sefair, J. A., Méndez, C. Y., Babat, O., Medaglia, A. L., & Zuluaga, L. F. (2017). Linear solution schemes for Mean-SemiVariance Project portfolio selection problems: An application in the oil and gas industry. Omega, 68, 39-48. https://doi.org/10.1016/j.omega.2016.05.007
Shariatmadari, M., Nahavandi, N., Zegordi, S. H., & Sobhiyah, M. H. (2017). Integrated resource management for simultaneous project selection and scheduling. Computers & Industrial Engineering, 109, 39-47. https://doi.org/10.1016/j.cie.2017.04.003
Shou, Y. Y., & Huang, Y. L. (2010). Combinatorial auction algorithm for project portfolio selection and scheduling to maximize the net present value. Journal of Zhejiang University SCIENCE C, 11(7), 562-574. https://doi.org/10.1631/jzus.C0910479
Smarandache, F. (2005). Neutrosophic set-a generalization of the intuitionistic fuzzy set. International Journal of Pure and Applied Mathematics, 24(3), 287.
Stummer, C., Kiesling, E., & Gutjahr, W. J. (2009). A multicriteria decision support system for competence-driven project portfolio selection. International Journal of Information Technology & Decision Making, 8(02), 379-401. https://doi.org/10.1142/S0219622009003429
Tang, B. J., Zhou, H. L., & Cao, H. (2017). Selection of overseas oil and gas projects under low oil price. Journal of Petroleum Science and Engineering, 156, 160-166. https://doi.org/10.1016/j.petrol.2017.05.022
Tavana, M., Keramatpour, M., Santos-Arteaga, F. J., & Ghorbaniane, E. (2015). A fuzzy hybrid project portfolio selection method using data envelopment analysis, TOPSIS and integer programming. Expert Systems with Applications, 42(22), 8432-8444. https://doi.org/10.1016/j.eswa.2015.06.057
Tavana, M., Shiraz, R. K., & Di Caprio, D. (2019). A chance-constrained portfolio selection model with random-rough variables. Neural Computing and Applications, 31(S2), 931-945. https://doi.org/10.1007/s00521-017-3014-8
Teller, J., & Kock, A. (2013). An empirical investigation on how portfolio risk management influences project portfolio success. International Journal of Project Management, 31(6), 817-829. https://doi.org/10.1016/j.ijproman.2012.11.012
Tofighian, A. A., Moezzi, H., Barfuei, M. K., & Shafiee, M. (2018). Multi-period project portfolio selection under risk considerations and stochastic income. Journal of Industrial Engineering International, 14(3), 571-584. https://doi.org/10.1007/s40092-017-0242-6
Urli, B., & Terrien, F. (2010). Project portfolio selection model, a realistic approach. International Transactions in Operational Research, 17(6), 809-826. https://doi.org/10.1111/j.1475-3995.2010.00762.x
Wang, B., & Song, Y. (2016). Reinvestment strategy-based project portfolio selection and scheduling with time-dependent budget limit considering time value of capital. In Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation (pp. 373-381). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-662-49370-0_39
Wang, C. S., & Chen, W. (2011, November). A fuzzy model for R&D project portfolio selection. In 2011 International Conference on Information Management, Innovation Management and Industrial Engineering (Vol. 1, pp. 100-104). IEEE. https://doi.org/10.1109/ICIII.2011.30
Wang, C., & Shou, Y. (2011, December). Application of real options in project portfolio selection. In 2011 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 848-853). https://doi.org/10.1109/IEEM.2011.6118036
Wen, J. (2010, November). The strategy-oriented project portfolio selection and management. In IEEE 2010 International Conference on E-Product E-Service and E-Entertainment (pp. 1-4). https://doi.org/10.1109/ICEEE.2010.5660739
Wu, Y., Xu, C., Ke, Y., Chen, K., & Sun, X. (2018). An intuitionistic fuzzy multi-criteria framework for large-scale rooftop PV project portfolio selection: Case study in Zhejiang, China. Energy, 143, 295-309. https://doi.org/10.1016/j.energy.2017.10.105
Xu, W., Liu, G., Li, H., & Luo, W. (2017). A study on project portfolio models with skewness risk and staffing. International Journal of Fuzzy Systems, 19(6), 2033-2047. https://doi.org/10.1007/s40815-017-0295-0
Yager, R. R. (2013). Pythagorean membership grades in multicriteria decision making. IEEE Transactions on Fuzzy Systems, 22(4), 958-965. https://doi.org/10.1109/TFUZZ.2013.2278989
Yan, S., & Ji, X. (2018). Portfolio selection model of oil projects under uncertain environment. Soft Computing, 22(17), 5725-5734. https://doi.org/10.1007/s00500-017-2619-2
Yang, F., Song, S., Huang, W., & Xia, Q. (2015). SMAA-PO: project portfolio optimization problems based on stochastic multicriteria acceptability analysis. Annals of Operations Research, 233(1), 535-547. https://doi.org/10.1007/s10479-014-1583-9
Yang, Y., & John, R. (2012). Grey sets and greyness. Information Sciences, 185(1), 249-264. https://doi.org/10.1016/j.ins.2011.09.029
Yu, L., Wang, S., Wen, F., & Lai, K. K. (2012). Genetic algorithm-based multi-criteria project portfolio selection. Annals of Operations Research, 197(1), 71-86. https://doi.org/10.1007/s10479-010-0819-6
Zaras, K., Marin, J. C., & Boudreau-Trude, B. (2012). Dominance-based rough set approach in selection of portfolio of sustainable development projects. American Journal of Operations Research, 2(04), 502-508. https://doi.org/10.4236/ajor.2012.24059
Zavadskas, E. K., Bausys, R., Kaklauskas, A., Ubarte, I., Kuzminske, A., & Gudiene, N. (2017a). Sustainable market valuation of buildings by the single-valued neutrosophic MAMVA method. Applied Soft Computing, 57, 74-87. https://doi.org/10.1016/j.asoc.2017.03.040
Zavadskas, E. K., Turskis, Z., Tamošaitiené, J., & Marina, V. (2008). Multicriteria selection of project managers by applying grey criteria. Technological and Economic Development of Economy, 14(4), 462-477. https://doi.org/10.3846/1392-8619.2008.14.462-477
Zavadskas, E. K., Turskis, Z., Vilutienė, T., & Lepkova, N. (2017b). Integrated group fuzzy multi-criteria model: Case of facilities management strategy selection. Expert Systems with Applications, 82, 317-331. https://doi.org/10.1016/j.eswa.2017.03.072
Zavadskas, E. K., Vilutienė, T., Turskis, Z., & Šaparauskas, J. (2014). Multi-criteria analysis of Projects’ performance in construction. Archives of Civil and Mechanical Engineering, 14(1), 114-121. https://doi.org/10.1016/j.acme.2013.07.006
Zhang, W. G., Mei, Q., Lu, Q., & Xiao, W. L. (2011). Evaluating methods of investment project and optimizing models of portfolio selection in fuzzy uncertainty. Computers & Industrial Engineering, 61(3), 721-728. https://doi.org/10.1016/j.cie.2011.05.003
Zhao, W., Wu, Q., & Wen, X. (2018, November). Research on the evaluation method of green construction project based on grey entropy correlation. In IOP Conference Series: Materials Science and Engineering (Vol. 439, No. 3, p. 032052). IOP Publishing. https://doi.org/10.1088/1757-899X/439/3/032052
Zhou, D., Huang, H., Teng, C., & Zhao, P. (2012). Project selection of robust portfolio models with incomplete information. Journal of Finance and Investment Analysis, 1(2), 157-199.
Zhou, X., Wang, L., Liao, H., Wang, S., Lev, B., & Fujita, H. (2019). A prospect theory-based group decision approach considering consensus for portfolio selection with hesitant fuzzy information. Knowledge-Based Systems, 168, 28-38. https://doi.org/10.1016/j.knosys.2018.12.029
Zhu, D., & Wang, X. (2012). A petroleum R&D project portfolio investment selection model with project interactions under uncertainty. Journal of Petroleum Science Research, 44-50. Retrieved from http://www.airitilibrary.com/Publication/alDetailedMesh?docid=P20150604011-201210-201508180020-201508180020-44-50
Zolfaghari, S., & Mousavi, S. M. (2018). Construction-project risk assessment by a new decision model based on De-Novo multi-approaches analysis and hesitant fuzzy sets under uncertainty. Journal of Intelligent and Fuzzy Systems, 35, 639-649. https://doi.org/10.3233/JIFS-162013