A multi- objective project portfolio selection and scheduling problem under uncertainty (case study: company of Payafanavaran Ferdowsi)

Document Type : Research Paper

Authors

1 Assistant Prof., Faculty of Industrial Engineering, Sadjad University of Technology, Mashhad, Iran

2 MSc. Student, Industrial Engineering, Sadjad University of Technology, Mashhad, Iran

Abstract

Nowadays organization especially R&D centers are dealing with project portfolio selection decisions under uncertainty. Moreover in the most of the past research, project portfolio selection and scheduling are often considered to be independent problem. This leads to insufficient result in real world. So in this research simultaneous project portfolio selection and scheduling problem is modeling whose objectives are maximizing expected profit and minimizing risk. Moreover there is autocorrelation among annual earnings. Therefore an efficient time series methodology is used for forecasting. Another advantage of proposed model is considering uncertainty of project success and earnings and also risk of dealing with budget deficiency. Due to the complexity of problem, especially for large size, practical swarm, simulated annealing and genetic algorithm are presented and their efficiency is compared by a hypothetical example. The results show efficiency of simulated annealing algorithm in terms of quality and execution time. Finally the model is validated via its application to a knowledge based company in Ferdowsi University of Mashhad.

Keywords


-          Abbassi, M., Ashrafi, M., & Sharifi Tashnizi, E. (2014). Selecting balanced portfolios of R&D projects with interdependencies: A Cross-Entropy based methodology. Technovation, 34(1): 54–63.
-          Baker, N. and Freeland, J. (1975). Recent advances in R&D benefit measurement and project selection methods. Management Science, 21(10): 1164-1175.
-          Carazo, A. F., Gómez, T., Molina, J., Hernández-Díaz, A. G., & Guerrero, F. M. (2010). Solving a Comprehensive model for multi-objective project portfolio selection. Computers & Operations Research, 37(4): 630 – 639.
-          Chen, J., & Askin, R. G. (2009). Project selection, scheduling and resource allocation with time dependent Returns. European Journal of Operational Research, 193(1): 23–34.
-          Coffin, M. A. & Taylor, B. (1996). Multiple criteria R&D project selection & Scheduling using fuzzy logic. Computers Operational Research, 23(3): 207-220.
-          Dickinson, M. W., Thornton, A. C., & Graves, S. (2001). Technology Portfolio Management: Optimizing Interdependent Projects over Multiple Time Periods. IEE Transaction on engineering management, 48(4): 518-527.
-          Dorri, B., Asadi, B. & Mazaheri, S. (2015). A Project Portfolio Selection Model with Project Interaction & Resources Interdependency Consideration Using Artificial Neural Networks. Journal of Industrial Management. 7(1): 21-42 (in Persian).
-          Fereydouni, S. and Moradian Boroujeni, P. (2012). A Fuzzy Simulated Annealing Model for Solving Chance Constrained Capital Budgeting Problem and Sensitivity Analysis of Parameters. Quarterly Journal of Operational Research and Its Applications (Journal of Applied Mathematics), 8(4): 13-27 (in Persian).
-          Ghasemzadeh, F., Archer, N., & Iyogun. (1999). A zero-one model for project portfolio selection and scheduling. Journal of the Operational Research Society, 50(7): 745-755.
-          Golmohammadi, A., & Pajoutan, M. (2011). Meta heuristics for dependent portfolio selection problem considering risk. Expert Systems with Applications, 38(5): 5642–5649.
-          Haung, X. and Zhao, T. (2014). Mean-chance model for portfolio selection based on uncertain measure. Insurance: Mathematics and Economics, 59: 243-250.
-          JafarNejad, A. and Yousefi Zenouz, R. (2008). A Fuzzy Model of Ranking Risks at Petropars Company’s Excavation of Oil Well Projects. Journal of Industrial Management, 1(1): 21-38 (in Persian).
-          Kalami- haris, M. (2014, 1 January). Solving Resource Constrained Project Scheduling Problem (RCPSP) in Matlab Software [video file]. Video Posted to http://www.matlabsite.com/503/mvror9102d-resource-constrained-project-scheduling-video-tutorial.html (in Persian).
-          Karp, R. M. (Eds.). (1972). Complexity of Computer Computation. Yorktown Heights, NY: Miller.
-          Liu, Sh. Sh., Wang, Ch-J. (2011). Optimizing project selection and scheduling problems with time-dependent resource constraints. Automation in Construction, 20(8): 110-1119.
-          Modares, A. and Abbaszadeh, M. R. (2008). An Analytic Study on Effect of Predictive Ability of Accruals and Cash Flows on Predicted Earnings Quality. Knowledge and Development, 15(24): 205- 239 (in Persian).
-          Mohaghar, A., Mehregan, M. R., Azar, A. & Motahari, N. (2015). Designing a Model for Selecting Construction Projects in Public Sector. Journal of Industrial Management. 6(4): 831-847 (in Persian).
-          Molavi. F. (2014). Proceedings of the 7th International Conference of Iranian Operations Research Society. Semnan University, Semnan: Iran (in Persian).
-          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.
-          Pourkazemi, M. H., Fattahi, M., Mazaheri, S. and Asadi, B. (2013). Project Portfolio Optimization with Considering Interaction between Projects Using Imperialist Competitive Algorithm (ICA). Journal of Industrial Management, 5(1): 1-20. (in Persian)
-          Rao, S. S., & Freiheit, T. I. (1991). A modified game theory approach to multiobjective optimization.Journal of Mechanical Design, 113(3): 286–291.
-          Sefair, J. A. & Medaglia, A. L. (Eds.). (2005). Proceedings of the Systems and Information Engineering Design Symposium. Charlottesville, Virginia USA: Bass.
-          Sun, H., Ma, T. (2005). A packing-multiple-boxes model for R&D project selection and scheduling. Technovation, 25(11): 1355-1361.
-          Zhu, H., Wang, Y., Wang, K., & Chen, Y. (2011). Particle Swarm Optimization (PSO) for the constrained portfolio optimization problem. Expert Systems with Applications, 38(8): 10161–10169.