A Linearization Approach for Project Selection with Interdependencies in Resource Costs

Ali Shafahi, Ali Haghani

Abstract

In this paper a new formulation is proposed for project selection problem which considers project interdependencies. Project interdependencies are factored in using the learning curve concept. The problem is modeled as a Mixed Integer Program (MIP) with quadratic constraints. To solve the problem the quadratic constraints are linearized using a new method proposed in this paper and the benefits of this approach compared to the conventional methods are emphasized. The application of this methodology is illustrated using a numerical example. The result shows the superiority of this method in reducing the number of variables dramatically.

References

  1. Anzanello, M. J. and Fogliatto, F. S. (2011). Learning curve models and applications: Literature review and research directions. International Journal of Industrial Ergonomics, 573-483.
  2. Bhattacharyya, R., Kumar, P. and Kar, S. (2011). Fuzzy R&D portfolio selection of interdependent projects. Computers & Mathematics with Applications, 3857- 3870.
  3. Carazo, A. F., Gomez, T., Molina, J., Hernandez-Diaz, A., Guerrero, F. and Caballero, R. (2010). Solving a Comperehensive model for Multi-Objective Project Selection . Computers and Operational Research, 630-639.
  4. Glover, F. and Woolsey, E. (1974). Converting the 0-1 polynomial programming problem to a 0-1 linear problem. Operations Research, 180-182.
  5. Iniestra, J. G. and Gutierrez, J. G. (2009). Multicriteria decisions on interdeendent infrastructure transportation projects using an evolutionary-based framework. Applied Soft Computing, 512-526.
  6. Killen, C. P. and Kjaer, C. (2012). Understanding project interdependencies: The role of visual representation, culture and process. International Journal of Project Management, 554-566.
  7. Lee, J. W. and Kim, S. H. (2000). Using analytical network process and goal programming for interdependent information system project selection. Computers & Operations Research, 367-382.
  8. Liesio, J., Mild, P. and Salo, A. (2008). Robust portfolio modeling with incomplete cost information and project interdependencies. European Journal of Operaional Research, 679-695.
  9. Liu, S.-S. and Wang, C.-J. (2011). Optimizing project selection and scheduling problems with timedependent resource constraints. Automation in Construction, 1110-1119.
  10. Santhanam, R. and Kyparisis, J. (1995). A multiple criteria decision model for information system project selection. Computers & Operations Research, 807- 818.
  11. Schmidt, R. L. (1993). A Model for R and D Project Selection with Combined Benefit, Outcome and Resource Interactions. IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 403-410.
  12. Snthanam, R. and Kyparisis, G. J. (1996). A decision model for interdependent information system project selection. European Journal of Operational Research, 380-399.
Download


Paper Citation


in Harvard Style

Shafahi A. and Haghani A. (2013). A Linearization Approach for Project Selection with Interdependencies in Resource Costs . In Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-8565-40-2, pages 230-235. DOI: 10.5220/0004214402300235


in Bibtex Style

@conference{icores13,
author={Ali Shafahi and Ali Haghani},
title={A Linearization Approach for Project Selection with Interdependencies in Resource Costs },
booktitle={Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2013},
pages={230-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004214402300235},
isbn={978-989-8565-40-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - A Linearization Approach for Project Selection with Interdependencies in Resource Costs
SN - 978-989-8565-40-2
AU - Shafahi A.
AU - Haghani A.
PY - 2013
SP - 230
EP - 235
DO - 10.5220/0004214402300235