IDEAS home Printed from https://ideas.repec.org/a/arp/tjssrr/2018p201-210.html
   My bibliography  Save this article

Fuzzy Optimization Models for Project Portfolio Rolling Planning Taking into Account Risk and Stakeholder Interests

Author

Listed:
  • Lev Solomonovich Mazelis*

    (Vladivostok State University of Economics and Service, Gogolya Street, 41, Vladivostok, 690014, Russia)

  • Konstantin Sergeevich Solodukhin

    (Vladivostok State University of Economics and Service, Gogolya Street, 41, Vladivostok, 690014, Russia)

  • Aleksandr Dmitrievich Tarantaev

    (Vladivostok State University of Economics and Service, Gogolya Street, 41, Vladivostok, 690014, Russia)

Abstract

Some modified fuzzy multiperiod optimization models are proposed to support decision-making when selecting a project portfolio within an institution’s strategic development program allowing for rolling planning of a project portfolio taking into account stakeholder interests and risks. Stakeholder interests are taken into consideration when setting strategic goals. Risk assessment is carried out in accordance with H. Markowitz portfolio theory using a scenario-based approach. A measure of portfolio risk is the fuzzy dispersion of its general specific utility. The developed models differ from the previously proposed fuzzy multiperiod models in possible revision of the composition of the previously selected project portfolio at every step depending on the already achieved results and changes in external and internal conditions. Another important difference is the introduction of additional fuzzy resource constraints for each time period, which are also revised at each step. In addition, constraints on fuzzy discounted costs are introduced and recalculated. Possible division of periods into subperiods is also taken into consideration. Also, at each step, fuzzy project costs are revised per period depending on whether the project is already included in the development program or not. The use of the proposed models is demonstrated based on the example of a university. Further research trends in this area are defined.

Suggested Citation

  • Lev Solomonovich Mazelis* & Konstantin Sergeevich Solodukhin & Aleksandr Dmitrievich Tarantaev, 2018. "Fuzzy Optimization Models for Project Portfolio Rolling Planning Taking into Account Risk and Stakeholder Interests," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 201-210:3.
    • Handle: RePEc:arp:tjssrr:2018:p:201-210
    as

    Download full text from publisher

    File URL: https://www.arpgweb.com/pdf-files/spi3.33.201.210.pdf
    Download Restriction: no
    File URL: https://www.arpgweb.com/journal/7/special_issue/12-2018/3/4
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Voss, Martin & Kock, Alexander, 2013. "Impact of Relationship Value on Project Portfolio Success - Investigating the Moderating Effects of Portfolio Characteristics and External Turbulence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63279, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Wang, Juite & Hwang, W.-L., 2007. "A fuzzy set approach for R&D portfolio selection using a real options valuation model," Omega, Elsevier, vol. 35(3), pages 247-257, June.
    3. Lean Yu & Shouyang Wang & Fenghua Wen & Kin Lai, 2012. "Genetic algorithm-based multi-criteria project portfolio selection," Annals of Operations Research, Springer, vol. 197(1), pages 71-86, August.
    Full references (including those not matched with items on IDEAS)

    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. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Li, Xinying & Li, Lingwenying, 2019. "Portfolio selection of distributed energy generation projects considering uncertainty and project interaction under different enterprise strategic scenarios," Applied Energy, Elsevier, vol. 236(C), pages 444-464.
    2. Chiara Oostuizen & Sara S. Grobbelaar & Wouter G. Bam, 2018. "Project Portfolio Management Best Practice and Implementation: A South African Perspective," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-24, August.
    3. Panos Xidonas & Haris Doukas & George Mavrotas & Olena Pechak, 2016. "Environmental corporate responsibility for investments evaluation: an alternative multi-objective programming model," Annals of Operations Research, Springer, vol. 247(2), pages 395-413, December.
    4. Driouchi, Tarik & Leseure, Michel & Bennett, David, 2009. "A robustness framework for monitoring real options under uncertainty," Omega, Elsevier, vol. 37(3), pages 698-710, June.
    5. Madjid Tavana & Mariya Sodenkamp & Leena Suhl, 2010. "A soft multi-criteria decision analysis model with application to the European Union enlargement," Annals of Operations Research, Springer, vol. 181(1), pages 393-421, December.
    6. T H Moon & Y Kim & S Y Sohn, 2011. "Technology credit rating system for funding SMEs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 608-615, April.
    7. Jung Ho Park & Kwangsoo Shin, 2018. "R&D Project Valuation Considering Changes of Economic Environment: A Case of a Pharmaceutical R&D Project," Sustainability, MDPI, vol. 10(4), pages 1-15, March.
    8. M Tavana & M A Sodenkamp, 2010. "A fuzzy multi-criteria decision analysis model for advanced technology assessment at Kennedy Space Center," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(10), pages 1459-1470, October.
    9. F. Perez & T. Gomez, 2016. "Multiobjective project portfolio selection with fuzzy constraints," Annals of Operations Research, Springer, vol. 245(1), pages 7-29, October.
    10. Barbati, Maria & Greco, Salvatore & Kadziński, Miłosz & Słowiński, Roman, 2018. "Optimization of multiple satisfaction levels in portfolio decision analysis," Omega, Elsevier, vol. 78(C), pages 192-204.
    11. Sameer Bathallath & Åsa Smedberg & Harald Kjellin, 2019. "The Viable System Model for Diagnosing and Handling IT-Project Interdependencies in Large Portfolios," International Journal of Information Technology Project Management (IJITPM), IGI Global, vol. 10(1), pages 72-87, January.
    12. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.
    13. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Chen, Kaifeng & Sun, Xiaokun, 2018. "An intuitionistic fuzzy multi-criteria framework for large-scale rooftop PV project portfolio selection: Case study in Zhejiang, China," Energy, Elsevier, vol. 143(C), pages 295-309.
    14. Hassanzadeh, Farhad & Collan, Mikael & Modarres, Mohammad, 2011. "A technical note on "A fuzzy set approach for R&D portfolio selection using a real options valuation model" by Wang and Hwang (2007)," Omega, Elsevier, vol. 39(4), pages 464-465, August.
    15. Hongjun Dai & Tao Sun & Wen Guo, 2016. "Brownfield Redevelopment Evaluation Based on Fuzzy Real Options," Sustainability, MDPI, vol. 8(2), pages 1-10, February.
    16. Selin Özpeynirci & Özgür Özpeynirci & Vincent Mousseau, 2021. "An interactive algorithm for resource allocation with balance concerns," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 983-1005, December.
    17. Theodor J. Stewart, 2016. "Multiple objective project portfolio selection based on reference points," Journal of Business Economics, Springer, vol. 86(1), pages 23-33, January.
    18. Karsu, Özlem & Morton, Alec, 2014. "Incorporating balance concerns in resource allocation decisions: A bi-criteria modelling approach," Omega, Elsevier, vol. 44(C), pages 70-82.
    19. Alibeiki, Hedayat & Lotfaliei, Babak, 2022. "To expand and to abandon: Real options under asset variance risk premium," European Journal of Operational Research, Elsevier, vol. 300(2), pages 771-787.
    20. Lo Nigro, Giovanna & Morreale, Azzurra & Enea, Gianluca, 2014. "Open innovation: A real option to restore value to the biopharmaceutical R&D," International Journal of Production Economics, Elsevier, vol. 149(C), pages 183-193.

    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:arp:tjssrr:2018:p:201-210. 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: Managing Editor (email available below). General contact details of provider: http://arpgweb.com/?ic=journal&journal=7&info=aims .

    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.