Network programming theory application to project portfolio formation

  • Irina Burkova
  • Boris Titarenko
  • Amir Hasnaoui
  • Titarenko Roman Synergy University, Russia
Keywords: project, project portfolio, network programming, generalized dual problem

Abstract


The paper deals with an application of the network (dichotomous) programming method for solving multi-extremal problems and discrete optimization problems. The concept of a generalized dual problem is introduced and a theorem on its convexity is proved. Network programming method is used to build a business-forming project portfolio as well as an algorithm for solving completely dependent related projects is developed. Also, this method is used to solve the problem of building a business-supporting project portfolio for which the lower cost estimate is obtained. A computational experiment is carried out to evaluate the suggested algorithm, which showed that for large dimensions of the problem it is more effective than for solving the problem by linear programming methods.

References

Archer, N., & Ghasemzadeh, F. (1999). An integrated framework for project portfolio selection. Int. J. Project Manage. 17 (4), 207–216.

Artto, K.A., Martinsuo, M., & Aalto, T. (2001). Project Portfolio Management: Strategic Management through Projects, Helsinki, FI: Project Management Association Finland.

Burkov, V., & Burkova, I. (2003). Dichotomous programming method in optimization problems. Moscow, Russia: Central Economic and Mathematical Institute of the Russian Academy of Sciences (in Russian).

Burkov, V., Burkova, I., Popok, M., & Ovchinnikova, T. (2005). Method of network programming. Annals of the Institute of Management Problems under V.A. Trapeznikov of the Russian Academy of Sciences, 3, 25-27 (in Russian).

Burkova, I. (2009). A method of network programming in problems of nonlinear optimization. Automation and Remote Control, 70 (10), 1606–1612.

Burkov, V., Korobets, B., Minaev, V. & Tsepkin, A. (2017). Models, methods and

mechanisms for managing scientific and technical programs. Moscow, Russia: Bauman Moscow State Technical University, 1–202 (in Russian).

Burkov, V., Kondratjev, V. & Tsepkin, A. (2011). Mechanisms for improving road safety. Editorial URSS, Moscow, RU: 1–208 [in Russian].

Coesmans, P., Fuster, M., Schreiner, J,G., Goncalves, M., Huynink, S., Jaques, T., Pugasevskis, V., Sedlmayer, M., Thyssen, D., Tovb, A., Vukomanovic, M., & Young, M. (2018). Individual Competence Baseline for project, program and portfolio management (version 4). Zurich, Switzerland: International Project Management Association.

Gutjahr, W. (2011). Optimal dynamic portfolio selection for projects under a competence development model. OR Spectrum, 33, 173-206.

Hyväri, I. (2014). Project portfolio management in a company strategy implementation, a case study. Procedia – Social and Behavioral Sciences, 119, 229–236.

Kondratjev, V. & Tsepkin, A. (2019). Project management in the implementation of the road safety strategy. Scientific edition of Moscow Automobile and Road Construction State Technical University, 4 (59), 112–119 [in Russian].

Levine, H.A. (2005). Project Portfolio Management. San Francisco, CA, USA: Jossey-Bass. Maizlish, B., & Handler, R. (2005). IT portfolio management step-by-step: unlocking the business value of technology. Hoboken, NJ, US: John Wiley & Sons.

Marcondes, G., Leme, R., & Silva, M. (2017). Using mean-Gini and stochastic dominance to choose project portfolios with parameter uncertainty. The Engineering Economist, 62 (1), 33–53.

Meredith, J.R., & Mandel, S.J. (2010). Project management: a managerial approach (7th ed.) Hoboken, NJ, US: John Wiley & Sons.

Momćilović, O., Djukic Petromanjanc, L., Doljanica, S., & Rajaković, J. (2014). Organizational context of project portfolio management. Annals of the University of Oradea, 3, 192–196.

Sharifghazvini, M. (2018). Integration of a new MCDM approach based on the DEA, FANP with MONLP for efficiency-risk assessment to optimize project portfolio by branch and bound: a real case study. Economic computation and Economic Cybernetics Studies and Research, 52 (1), 261–278.

Tavano, M., Khalili, K., & Abtahi, A.-R. (2013). A fuzzy multidimensional multiple-choice knapsack model for portfolio selection using an evolutionary algorithm. Annals of Operations Research, 206, 449–483.

Titarenko, B., Hasnaoui, A., Titarenko, R., & Buzuk, L. (2018). Robust data analysis in innovation project portfolio management. SPbWOSCE-2017, MATEC Web of Conferences 170, 01017.

Turner, J. R., & Müller, R. (2003). On the nature of the project as a temporary organization. International Journal of Project Management, 21, 1–7.

Qingguo, T. (2015). Robust estimation for spatial semiparametric varying coefficient partially linear regression. Stat Papers 56, 1137–1161.

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, 535 –547.

Yousefi, V., Yakchali, S., Saparauskas, J., & Kiani, S. (2018). The impact made on Project Portfolio optimisation by selection of various risk measures. Inzinerine Ekonomika-Engineering Economics, 29 (2), 168–175.

Yu, L., Wen, S.W., & Lay, K.K. (2012). Genetic algorithm-based multi-criteria project portfolio selection. Annals of Operations Research, 197 (1), 71–86.

Published
2021/06/03
Section
Original Scientific Paper