Developing and solving a two-stage Optimization Model for project Portfolio selection and scheduling in uncertain conditions
Subject Areas :
Tahereh Heydari
1
,
seyed mohammad seyedhosseini
2
,
Ahmad Makui
3
1 - University of Science and Technology
2 - University of Science and Technology
3 - Iran University of Science and Technology
Keywords: project portfolio Fuzzy PROMTHEE method two stage model project selection and scheduling,
Abstract :
Because of limited resources, organizations, often, have to make crucial decisions regarding selection and scheduling of a project portfolio among the candidate projects. A poor decision might affect the organization in two ways: First, by wasting the organization’s resources (monetary cost), investing them in weak and non-strategic projects and second, by losing the opportunity to invest the resources in more profitable projects (opportunity cost). Hence, selecting a rich portfolio has been always an important role of project managers. In this article, a two-phased model for portfolio project selection in fuzzy conditions is presented; in the first phase by using fuzzy PROMTHEE method, alternative are ranked and in the second phase alternative with higher rank, concerning restrictions are selected and scheduled
E. Afful-Dadzie, Z.K. Oplatková, S. Nabareseh, “Selecting Start-Up Businesses in a Public Venture Capital Financing using Fuzzy PROMETHEE” Procedia Computer Science 60, ( 2015 ), 63 – 72
A. Albadvi., S.K. Chaharsooghi., A. Esfahanipour, : “Decision making in stock trading: an application of PROMETHEE”. Eur. J. Oper. Res. 177(2), (2007), pp 673–683.
R. Bellman, L.A. Zadeh,. “Decision making in fuzzy environment”. Management Science 17, (1970), pp141-164.
R.U . Bilsel., G. Buyukozkan, D. Ruan, : “A fuzzy preference ranking model for a quality evaluation of hospital web sites”, In. J. Intell. Syst. 21(11), (2006), pp 1181–1197
Bo Feng. Jian, Ma. ,Zhi- Ping, Fan.: An integrated method for collaborative R&D project selection: Supporting innovative research teams”, Expert System with Applications, pp. 5532-5543, (2010)
J-P. Brans, B. Mareschal ,“Multiple Criteria Decision Analysis , Chapter 5: PROMETHEE METHODS”.pp.163-195
J-P. Brans, B. Mareschal, P. Vincke. “PROMETHEE:a new family of outranking methods in multi criteria analysis”. In: Brans J,editor.Operational research’84. Amsterdam: North-Holland, (1984), pp.477–490
J-P. Brans, P. Vincke, B. Mareschal,. “How to select and how to rank projects: The PROMETHEE method”. European Journal of Operational Research 24, (1986), pp. 228-238
J-P. Brans, B. Mareschal. “PROMETHEE methods. In: Figueira J, GrecoS, Ehrgott M, editors .Multiple criteria decision analysis—state of theart surveys .New York: Springer, (2005) pp.163–95
J. Buckley,: “Ranking alternatives using fuzzy numbers”. Fuzzy sets and systems, vol. 15, no. 1, (1985), pp. 21–31
A.F. Carazo, Trinidad, Gómez. , Julián, Molina., Alfredo, G.Hernández- Díaz., &Flor, M. Guerrero.: Solving a comprehensive model for multi objective project portfolio selection. Computers & Operations Research, 630-639, (2010)
C. Carlsson, R. Fullér, M. Heikkilä, P. Majlender,: A fuzzy approach to R&D project portfolio selection. International Journal of Approximate Reasoning, pp. 93-105, (2007)
P.T. Chang, j.H. Lee,: A fuzzy DEA and knapsack formulation integrated model for project selection. Computers & Operations Research, 39, (2012), pp. 112–125
S.H. Chen, “Ranking fuzzy numbers with maximizing set and minimizing set,” Fuzzy Sets and Systems, Vol.17, No.2, (1985), pp.113-129
Y.H. Chen , T.Ch. Wang, Ch.Y Wu; “Strategic decisions using the fuzzy PROMETHEE for IS outsourcing” Expert Systems with Applications 38 (2011) 13216-13222
Dubois, D., Prade, H. “Operations on fuzzy numbers”. International Journal of Systems Science 9, (1978), pp. 613-626
Dubois, D., Prade, H., “Fuzzy real algebra: Some results”. Fuzzy Sets and Systems 2, (1979), pp. 327-348
Dubois, D., Prade H., “Possibility Theory. An Approach to Computerized Processing of Uncertainty”. Plenum Press, New York. (1988)
F. Fülöp,: Introduction to Decision Making Methods. Laboratory of Operations Research and Decision Systems. Computer Automation Institute, Hungarian Academy of Sciences
M. Goumas, V. Lygerou,: An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects, European Journal of Operational Research, 123, (2000), pp. 606-613
Huang, Chi-Cheng., Chu , Pin-Yu., Chiang, Yu-Hsiu.: A fuzzy AHP application in government- sponsored R&D project selection. Omega, (2008), pp. 1038-1052,
C.L. Hwang, k. Yoon,: Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, New York, (1981).
B. Jafarizadeh, R. RamazaniKhorshid –Dust,: A method of project selection based on capital asset pricing theories in a framework of mean- semideviation behavior. International Journal of Project Management, (2008), pp. 612-619
P. Jana,: Multi objective mean-variance- skewness model for portfolio optimization. AMo- advanced Modeling and Optimization, (2007)
YP. Jiang,: A method for group decision making with multi- granularity linguistic assessment information, Information Sciences, vol. 178, no. 4, (2008), pp. 1098–1109
Jiaqiong, Chen., Ronald, G. Askin.: project selection, scheduling and resource allocation with time dependent returns. European Journal of Operational Research, (2009), pp. 23-34,
P. Kumar-Dey,: Integrated project evaluation and selection using multiple attribute decision making technique. Int. J. Production Economics, (2006), pp 90-103.
H. Markowitz,: Portfolio selection. Journal of Finance, vol 7, No 1, (1952), pp. 77-91.
H. Markowitz,: Portfolio selection: Efficient diversification of investments. NewYork: Wiley, (1959)
J.C. Pomerol, S. Barba-Romero,: Multi criterion decision in management: principles and practice. Dordrecht: Kluwer Academic Publishers; (2000)
M. Rabbani, R.TavakkoliMoghaddam, F. Jolai, H.R. Ghorbani,: A Comprehensive Model For R And D Project Portfolio Selection With zero-One Linear Goal Programming. IJE Transactions A: Basics, pp 55-64,
O. Senvar, G.Tuzkaya and C .Kahraman,: “Multi Criteria Supplier Selection Using Fuzzy PROMETHEE Method”, 2014, Supply Chain Management Under Fuzziness, Studies in Fuzziness and Soft Computing 313, (2014), pp 21-34
S. Solak., J. Clarke. , E. L. Johnson. , & E. R. Barnes.: Optimization of R&D project portfolio under endogenous uncertainty. European Journal of Operational Research, (2010), pp. 420-433.
S. Suresh Kumar.: AHP based formal system for R&D project evaluation. Journal of Scientific& Industrial Research, (2004), pp. 888-896.
TarjaJoro, Paul Na.: Portfolio performance evaluation in a mean-variance- skewness framework. European Journal of Operational Research, (2006), pp. 446-461.
F. Tiryaki, B. Ahlatcioglu,: “Fuzzy portfolio selection using fuzzy analytic hierarchy process”. Information Science, (2009), pp. 53-69.
G. Tuzkaya, B. Gülsün, C. Kahraman, D. Özgen,: “An integrated fuzzy multi-criteria decision making methodology for material handling equipment selection problem and an application”. Expert Syst. Appl. 37(4), (2010), pp 2853–2863
R. Vetschera, Adiel .Teixeirade. Almeida.: A PROMETHEE-based approach to portfolio selection problems. Computers & Operations Research,39, (2012), pp 1010–1020.
T.Ch. Wang, L.Y. Chen, Y.H. Chen, “Applying Fuzzy PROMETHEE Method for Evaluating IS Outsourcing Suppliers, Fifth International Conference on Fuzzy Systems and Knowledge Discovery, (2008), pp 361- 365
Ma. Wanli,: “Research on portfolio optimization of agricultural intellectual property promotion engineering projects”. System Engineering Procedia, (2011), pp. 324-330.
B.Yilmaz, M. Dagdeviren, “A combined approach for equipment selection: F-PROMETHEE method and zero–one goal programming” Expert Systems with Applications 38 (2011) 11641–116
Yong Fang, Lihua Chen, Masao Fukushima.: A mixed R&D projects and securities portfolio selection model. European Journal of Operational Research, (2008), pp. 700-715.
L.A. Zadeh. “Fussy sets”. Information and Control 8, (1965), pp 338-353. W.G. Zhang, W.A. Liu, Y.L. Wang,: “On admissible efficient portfolio selection: Models and algorithms”. Applied Mathematics and Computation, (2006), pp. 208-218.