MODEL AND METHOD FOR SYNTHESIS OF PROJECT MANAGEMENT METHODOLOGY WITH FUZZY INPUT DATA

Igor V. KONONENKO, Ahmad AGHAEE

Abstract


Literature analysis concerning the selection or creation a project management methodology is performed. Creating a "complete" methodology is proposed which can be applied to managing projects with any complexity, various degrees of responsibility for results and different predictability of the requirements. For the formation of a "complete" methodology, it is proposed to take the PMBOK standard as the basis, which would be supplemented by processes of the most demanding plan driven and flexible Agile Methodologies. For each knowledge area of the PMBOK standard, The following groups of processes should be provided: initiation, planning, execution, reporting, and forecasting, controlling, analysis, decision making and closing. The method for generating a methodology for the specific project is presented. The multiple criteria mathematical model and method aredeveloped for the synthesis of methodology when initial data about the project and its environment are fuzzy. 

Keywords


project management methodology; Fuzzy multiple criteria decision making; synthesis method.

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References


Ilas, M. E., Ionescu, S &. Ilas, C. (2011). Selecting the appropriate project management process for R&D projects in microelectronics. U.P.B. Sci. Bull. Series C. Vol. 73. Iss. 1. 105–116.

Spundak, M. (2013). Mixed agile/traditional project management methodology – reality or illusion? 27th IPMA (International Project Management Association), World Congress, Dubrovnik, Croatia. Procedia Social and Behavioral Sciences.Vol. 119. 19 March 2014. 939–948 doi:10.1016/j.sbspro.2014.03.105

Il'ina, O. N. (2011). Metodologija upravlenija proektami: stanovlenie, sovremennoe sostojanie i razvitie [Project Management Methodology: formation, current status and development]. Moscow : INFRA-M : Vuzovskij uchebnik, 208 [in Russian].

Charvat, J. (2003). Project Management Methodologies: Selecting, Implementing, and Supporting Methodologies and Processes for Projects. John Wiley & Sons, INC, 264.

Cheema, A. & Arshad, A. A. (2005). Customizing project management methodology. 9th International Multitopic Conference, IEEE INMIC, Karachi, 1–6. doi:10.1109/INMIC.2005.334390

Kononenko, I. & Kharazii, A. (2014). The methods of selection of the project management methodology. International Journal of Computing,. Vol. 13, 4, 240–247.

Kononenko, I. V. & Aghaee, A. (2015). Syntez metodolohyy dlia upravlenyia proektom. [Synthesis of methodology for project management] Upravlinnia proektamy: stan ta perspektyvy: materialy ХІ Mizhnarodnoi naukovo-praktychnoi konferentsii. Project Management: Status and Prospects: Materials of XI International scientific-practical conference. – Mykolaiv: NUK, 73-74 [in Russian].

Raskin, L. G. & Seraja, O. V. (2008). Nechetkaja matematika. Osnovy teorii. Prilozhenija [Fuzzy Mathematics. Fundamentals of the theory. Applications]. Kharkiv : Parus, 352 [in Russian].

Leonenkov, A. (2005). Nechetkoe modelirovanie v srede Matlab i fuzzyTECH. [Fuzzy modeling in Matlab and fuzzyTECH] SPb. : BHV-Peterburg, 736 [in Russian].

Mihalevich, V. S. & Volkovich, V.L. (1982). Vychislitel'nye metody issledovanija i proektirovanija slozhnyh system. [Computational methods of complex systems research and design]. Moscow : Nauka, 286 [in Russian].

Ibragimov, V. A. (2009). Jelementy nechetkoj matematiki. [Elements of fuzzy mathematics]. Azerbajdzhanskaja gosud. neftjanaja akademija Baku, 391 [in Russian].

Haptahaeva, N. B., Dambaeva, S. V. & Ajusheeva N. N. (2004). Vvedenie v teoriju nechetkih mnozhestv [Introduction to the theory of fuzzy sets]. Ulan-Udje, Izdatel'stvo VSGTU, 68 [in Russian].

Pavlov, A. N. & Sokolov, B. V. (2006) Prinjatie reshenij v uslovijah nechetkoj informacii [Decision making under fuzzy information] SPb. : GUAP, 72 [in Russian].


GOST Style Citations


1. Ilas, M. E., Ionescu, S &. Ilas, C. (2011). Selecting the appropriate project management process for R&D projects in microelectronics. U.P.B. Sci. Bull. Series C. Vol. 73. Iss. 1. 105–116.

2. Spundak, M. (2013). Mixed agile/traditional project management methodology – reality or illusion? 27th IPMA (International Project Management Association), World Congress, Dubrovnik, Croatia. Procedia Social and Behavioral Sciences.Vol. 119. 19 March 2014. 939–948 doi:10.1016/j.sbspro.2014.03.105 

3. Il'ina, O. N. (2011). Metodologija upravlenija proektami: stanovlenie, sovremennoe sostojanie i razvitie [Project Management Methodology: formation, current status and development].Moscow: INFRA-M: Vuzovskij uchebnik, 208 [in Russian].

4. Charvat, J. (2003). Project Management Methodologies: Selecting, Implementing, and Supporting Methodologies and Processes for Projects. John Wiley & Sons, INC, 264.

5. Cheema, A. & Arshad, A. A. (2005). Customizing project management methodology. 9th International Multitopic Conference, IEEE INMIC, Karachi, 1–6. doi: 10.1109/INMIC.2005.334390

6. Kononenko, I. & Kharazii, A. (2014). The methods of selection of the project management methodology. International Journal of Computing,. Vol. 13, 4, 240–247.

7. Kononenko, I. V. & Aghaee, A. (2015). Syntez metodolohyy dlia upravlenyia proektom. [Synthesis of methodology for project management]Upravlinnia proektamy: stan ta perspektyvy: materialy ХІ Mizhnarodnoi naukovo-praktychnoi konferentsii. Project Management: Status and Prospects: Materials of XI International scientific-practical conference. – Mykolaiv: NUK, 73-74 [in Russian].

8. Raskin, L. G. & Seraja, O. V. (2008). Nechetkaja matematika. Osnovy teorii. Prilozhenija [Fuzzy Mathematics. Fundamentals of the theory. Applications]. Kharkiv : Parus, 352 [in Russian].

9. Leonenkov, A. (2005). Nechetkoe modelirovanie v srede Matlab i fuzzyTECH. [Fuzzy modeling in Matlab and fuzzyTECH] SPb. : BHV-Peterburg, 736 [in Russian].

10. Mihalevich, V. S. & Volkovich, V.L. (1982). Vychislitel'nye metody issledovanija i proektirovanija slozhnyh system. [Computational methods of complex systems research and design]. Moscow : Nauka, 286 [in Russian].

11. Ibragimov, V. A. (2009). Jelementy nechetkoj matematiki. [Elements of fuzzy mathematics]. Azerbajdzhanskaja gosud. neftjanaja akademija Baku, 391 [in Russian].

12. Haptahaeva, N. B., Dambaeva, S. V. & Ajusheeva N. N. (2004). Vvedenie v teoriju nechetkih mnozhestv [Introduction to the theory of fuzzy sets]. Ulan-Udje, Izdatel'stvo VSGTU, 68 [in Russian].

13. Pavlov, A. N. & Sokolov, B. V. (2006) Prinjatie reshenij v uslovijah nechetkoj informacii [Decision making under fuzzy information] SPb. : GUAP, 72 [in Russian].





DOI: https://doi.org/10.20998/2413-3000.2016.1173.2

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