Project Portfolio Scheduling as a Multiple-Criteria Decision Making Problem

• Autorzy: Bogumiła Krzeszowska
• Języki publikacji: EN

Abstrakty

EN

A new methodology for project portfolio scheduling problem has been presented in this paper. This methodology delivers information about project portfolio schedule, which is important for project portfolio managers. The methodology consists of three steps: multiple-criteria mathematical model building, finding non-dominated solutions and choosing one solution from the Pareto set as the final solution. In the first step a multiple-criteria mathematical model for project portfolio scheduling problem is built. Three criteria are considered in the model: the penalty for projects delays minimization, the penalty for resources overusage minimization and NPV maximization. Disadvantage of proposed mathematical model is a big amount of variables, which is J×T×P. In cases when we will have larger projects or larger planning horizon the number of variables will be huge. That is why activities aggregation was proposed. It reduces a number of variables in given model. It also delivers a general information about project portfolio schedule, which is more important for project portfolio managers. In the second step a set of non-dominated solutions is identified by using an elitist evolutionary algorithm. As research shows using an external set with the best solutions in each generation increases an algorithm efficiency. In the third step the LBS procedure is used to identify the final solution. The LBS procedure proposes is a way of learning-oriented interactive search for the best compromise solution for the decision maker. This procedure makes the comparison of non-dominated solution in the decision phase relatively easy. So this step will not burden the decision maker too much. For the future work, the procedure presented in this paper will be applied to the problem described in the section two, and given results will be compared with the current situation in the company. (fragment of text)

Słowa kluczowe

EN

Multicriteria analysis; Decision making; Multiple-criteria decision making; Project Portfolio Management (PPM)

PL

Analiza wielokryterialna; Podejmowanie decyzji; Wielokryterialne podejmowanie decyzji; Zarządzanie portfelem projektów

• Czasopismo: Studia Ekonomiczne / Uniwersytet Ekonomiczny w Katowicach
• Rocznik: 2013
• Numer: nr 137 Project planning in modern organization
• Strony: 69--82

Twórcy

autor

Bogumiła Krzeszowska

• University of Economics in Katowice, Poland

Bibliografia

• Carlier J., Chretienne P. (1988), Problemes d'ordonnancement: modelisation /complexite /algoitmes. Masson, Paris.
• Chiu H.N., Tai D.M. (2002), An efficient search procedure for the resourceconstrained multi-Project scheduling problem with discounted cash flows. "Construction Management and Economics", 20:55-66.
• Goncalves J.F., Mendes J.J., Resende M.G.C. (2004), A genetic algorithm for the resource constrained multi-project scheduling problem. AT and T labs. Technical Report TD-668 LM4.
• Hapke M., Jaszkiewiecz A., Słowiński R. (1998), Interactive analysis of multiple-criteria project scheduling problems. "European Journal of Operational Research" 107: s. 315- 324.
• Icmeli O., Erenguc S.S. (1996), A branch and bound procedure for the resource constrained project scheduling problem with discounted cash flows. "Management Science" 42(10):1395-1408.
• Jaszkiewicz A., Słowiński R. (1999), The Light Beam Search approach - an overview of methodology and applications. "European Journal of Operation Research" 113.
• Leu S.S., Yang C.H. (1999), Ga-based multicriteria optimal model for construction scheduling. "Journal of Construction Engineering and Management" 125(6): 420-427.
• Lova A., Maroto C., Tormos P. (2000), A multicriteria heuristic method to improve resource allocation in multiproject scheduling. "European Journal of Operational Research" 127: 408-424.
• Pinedo M. (1995), Scheduling - theory, Algorithms and Systems. Prentice Hall Englewood Cliffs.
• Viana. A., de Sousa J.P. (2000), Using metaheuristic in multiobjective resource constrained project scheduling. "European Journal of Operational Research" 120: 359-374.
• Zitzler E., Laumanns M., Thiele L. (2001), SPEA2 Improving the Strength Pareto Evolutionary Approach. Technical Report 103. Computer Engineering and Communication Networks Lab (TIK). Swiss Federal Institute of Technology (ETH) Zurich, Gloriastrasse 35, CH-8092 Zurich.