A comprehensive framework for project selection problem under uncertainty and real-world constraints

This paper proposes a comprehensive framework for project selection problem under uncertainty and subject to real-world constraints, like segmentation, logical, and budget constraints. The framework consists of two main phases. In the first phase, the candidate projects are ranked considering the uncertainty, through a Monte Carlo simulation linked to a multi-criteria approach. In the second phase, the overall complete preorder of the projects in different iterations is first determined and then used in another Monte Carlo simulation linked to an integer programming module in order to effectively drive the final portfolio selection while satisfying the budget, segmentation and other logical constraints. The proposed framework is implemented in a case study to show its usefulness and applicability in practice. Finally, a comparison is carried out between the proposed approach and its deterministic counterpart and the corresponding results are discussed.

[1]  A. D. Henriksen,et al.  A practical R&D project-selection scoring tool , 1999 .

[2]  Francis M. Lesusky,et al.  The development of a knowledge-based system for information systems project development consulting , 1987 .

[3]  Wann-Ming Wey.  A Multiobjective Optimization Model for Urban Renewal Projects Selection with Uncertainty Considerations , 2008, 2008 Fourth International Conference on Natural Computation.

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

[5]  D. Milosevic,et al.  Project portfolio selection: From past to present , 2008, 2008 4th IEEE International Conference on Management of Innovation and Technology.

[6]  Luís Vladares Tavares,et al.  A review of the contribution of Operational Research to Project Management , 2002, Eur. J. Oper. Res..

[7]  Qing Li,et al.  Enterprise information system project selection with regard to BOCR , 2008 .

[8]  Kumares C. Sinha,et al.  Methodology for Multicriteria Decision Making in Highway Asset Management , 2004 .

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

[10]  Risto Lahdelma,et al.  Comparing multicriteria methods in the context of environmental problems , 1998 .

[11]  Navee Chiadamrong,et al.  An integrated fuzzy multi-criteria decision making method for manufacturing strategies , 1999 .

[12]  Suresh K. Khator,et al.  Portfolio selection through mathematical programming in CAD environment , 1996 .

[13]  Kamran Rezaie,et al.  Safety interval analysis: A risk-based approach to specify low-risk quantities of uncertainties for contractor's bid proposals , 2009, Comput. Ind. Eng..

[14]  Rory Burke,et al.  Project Management: Planning and Control , 1994 .

[15]  Ruby Blasak,et al.  Selected microcomputer applications for hospital management engineers , 1987 .

[16]  Zongzhi Li,et al.  Highway Project Level Life-Cycle Benefit/Cost Analysis under Certainty, Risk, and Uncertainty: Methodology with Case Study , 2009 .

[17]  Young H. Park,et al.  Investment decisions: an integrated economic and strategic approach , 1990 .

[18]  Jin Wang,et al.  Research on project selection system of pre-evaluation of engineering design project bidding , 2009 .

[19]  Zongzhi Li.  Stochastic Optimization Model and O(N2) Solution Algorithm for Highway Investment Decision Making under Budget Uncertainty , 2009 .

[20]  M. Buss.  How to rank computer projects. , 1983, Harvard business review.

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

[22]  Andrés L. Medaglia,et al.  Models & Methods for Project Selection: Concepts from Management Science, Finance and Information Technology , 2012 .

[23]  Seungwoo Seo,et al.  A matrix approach for telecommunications technology selection , 1997 .

[24]  Kamran Rezaie,et al.  Using extended Monte Carlo simulation method for the improvement of risk management: Consideration of relationships between uncertainties , 2007, Appl. Math. Comput..

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

[26]  Renzo Rosso,et al.  Statistics, Probability and Reliability for Civil and Environmental Engineers , 1997 .

[27]  Matthew J. Liberatore,et al.  An extension of the analytic hierarchy process for industrial R&D project selection and resource allocation , 1987, IEEE Transactions on Engineering Management.

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

[29]  Jonathan F. Bard,et al.  An interactive approach to R&D project selection and termination , 1988 .

[30]  A. Charnes,et al.  A Chance-Constrained Model for Real-Time Control in Research and Development Management , 1966 .

[31]  Ronald G. Askin,et al.  Forming effective worker teams with multi-functional skill requirements , 2005, Comput. Ind. Eng..

[32]  Reza Baradaran Kazemzadeh,et al.  PROMETHEE: A comprehensive literature review on methodologies and applications , 2010, Eur. J. Oper. Res..

[33]  Chen-Tung Chen,et al.  A comprehensive model for selecting information system project under fuzzy environment , 2009 .

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

[35]  Jean Pierre Brans,et al.  HOW TO SELECT AND HOW TO RANK PROJECTS: THE PROMETHEE METHOD , 1986 .

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

[37]  J. Martino.  Research and Development project selection , 1995 .

[38]  Andrés L. Medaglia,et al.  A multiobjective evolutionary approach for linearly constrained project selection under uncertainty , 2007, Eur. J. Oper. Res..