The trichotomic approach for dealing with uncertainty in project portfolio selection: combining MCDA, mathematical programming and Monte Carlo simulation

Project portfolio selection refers to the problem of selecting a certain number from a wide set of proposed projects. In this work, we also address inherent uncertainty, present either in project characteristics (e.g., costs, performances) or in decision environment (e.g., criteria weights, total budget). We model uncertainty with probability distributions and we use Monte Carlo simulation to produce MCDA parameters as well as parameters for mathematical programming model. In this way, set of projects is divided into three subsets: 'green' projects that are always present in portfolio, 'red' projects that are never selected and 'grey' projects that are selected in some of Monte Carlo runs. Subsequently, the focus is moved on grey projects for further elaboration. The so called trichotomic approach offers much more fruitful information to the decision maker as it quantifies the degree of certainty with which each project is selected or not in the final portfolio.

[1]  Seyed Hossein Iranmanesh,et al.  A comprehensive framework for project selection problem under uncertainty and real-world constraints , 2011, Comput. Ind. Eng..

[2]  D. Vose.  Risk Analysis: A Quantitative Guide , 2000 .

[3]  Kampan Mukherjee,et al.  Application of goal programming in project selection decision -- A case study from the Indian coal mining industry , 1995 .

[4]  B. Mareschal,et al.  Water resources planning in the Middle East: application of the PROMETHEE V multicriteria method , 1995 .

[5]  D. Diakoulaki,et al.  Design and implementation of a group DSS for sustaining renewable energies exploitation , 1998, Eur. J. Oper. Res..

[6]  Tommi Tervonen,et al.  Implementing stochastic multicriteria acceptability analysis , 2007, Eur. J. Oper. Res..

[7]  George Mavrotas,et al.  Combined MCDA–IP Approach for Project Selection in the Electricity Market , 2003, Ann. Oper. Res..

[8]  L. J. Savage,et al.  Three Problems in Rationing Capital , 1955 .

[9]  Theodor J. Stewart,et al.  Multiple Criteria Decision Analysis , 2001 .

[10]  Mir-Bahador Aryanezhad,et al.  A modular Decision Support System for optimum investment selection in presence of uncertainty: Combination of fuzzy mathematical programming and fuzzy rule based system , 2011, Expert Syst. Appl..

[11]  Holger R. Maier,et al.  Incorporating uncertainty in the PROMETHEE MCDA method , 2003 .

[12]  David Vose,et al.  Quantitative Risk Analysis: A Guide to Monte Carlo Simulation Modelling , 1996 .

[13]  Richard H. Bernhard.  Mathematical Programming Models for Capital Budgeting—A Survey, Generalization, and Critique , 1969 .

[14]  Sundeep Sahay,et al.  A review of program evaluation and fund allocation methods within the service and government sectors , 1995 .

[15]  Risto Lahdelma,et al.  SMAA - Stochastic multiobjective acceptability analysis , 1998, Eur. J. Oper. Res..

[16]  Theodor J. Stewart,et al.  Multiple criteria decision analysis - an integrated approach , 2001 .

[17]  Wade D. Cook,et al.  Project prioritization: a resource-constrained data envelopment analysis approach , 2000 .

[18]  Radhika Santhanam,et al.  A DECISION MODEL FOR INTERDEPENDENT INFORMATION SYSTEM PROJECT SELECTION , 1996 .

[19]  Anthony E. Gear,et al.  Multistage Capital Budgeting under Uncertainty , 1975 .

[20]  George Mavrotas,et al.  Selection among ranked projects under segmentation, policy and logical constraints , 2008, Eur. J. Oper. Res..

[21]  Muhittin Oral,et al.  Project evaluation and selection in a network of collaboration: A consensual disaggregation multi-criterion approach , 2001, Eur. J. Oper. Res..

[22]  Kamal Golabi,et al.  Selecting a Portfolio of Solar Energy Projects Using Multiattribute Preference Theory , 1981 .

[23]  Muhittin Oral,et al.  A methodology for collective evaluation and selection of industrial R&D projects , 1991 .

[24]  Ahti Salo,et al.  Preference programming for robust portfolio modeling and project selection , 2007, Eur. J. Oper. Res..

[25]  George Mavrotas,et al.  Application in a Students’ Selection Problem , 2009, J. Decis. Syst..

[26]  Günter Fandel,et al.  Redistribution of funds for teaching and research among universities: The case of North Rhine-Westphalia , 2001, Eur. J. Oper. Res..

[27]  George Mavrotas,et al.  Project prioritization under policy restrictions. A combination of MCDA with 0-1 programming , 2006, Eur. J. Oper. Res..

[28]  N. K. Kwak,et al.  A multicriteria decision-making approach to university resource allocations and information infrastructure planning , 1998, Eur. J. Oper. Res..

[29]  Ahti Salo,et al.  Robust portfolio modeling with incomplete cost information and project interdependencies , 2008, Eur. J. Oper. Res..

[30]  Masood A. Badri,et al.  A comprehensive 0-1 goal programming model for project selection , 2001 .

[31]  Marc J. Schniederjans,et al.  A zero-one goal programming approach for information system project selection , 1989 .

[32]  K. Heidenberger.  Dynamic project selection and funding under risk: A decision tree based MILP approach , 1996 .

[33]  S. Christian Albright.  Allocation of research grants to university research proposals , 1975 .