How to cite this paper
Pour, B., Noori, S & Atashgah, R. (2013). Project selection problem under uncertainty: An application of utility theory and chance constrained programming to a real case.International Journal of Industrial Engineering Computations , 4(3), 373-385.
Refrences
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Akbari, R., Zeighami, V., & Ziarati, K. (2011). Artificial bee colony for resource constrained project scheduling problem. International Journal of Industrial Engineering Computations, 2(1), 45-60.
Angelelli, E., Mansini, R., & Grazia Speranza, M. (2010). Kernel search: A general heuristic for the multi-dimensional knapsack problem. Computers & Operations Research, 37(11), 2017-2026.
Anscombe, F. J., & Aumann, R. J. (1963). A definition of subjective probability. Annals of mathematical statistics, 34, 199-205.
Birge, J.R. & Louveaux, F. (1997). Introduction to Stochastic Programming. Springer, New York.Charnes, A. & Cooper, W.W. (1959). Chance-constrained programming. Management Science, 6, 73–79.
De, P. K., Acharya, D., & Sahu, K. C. (1982). A chance-constrained goal programming model for capital budgeting. Journal of the Operational Research Society, 33, 635-638.
Fang, Y., Chen, L., & Fukushima, M. (2008). A mixed R & D projects and securities portfolio selection model. European Journal of Operational Research,185(2), 700-715.
Feller, W. (2008). An introduction to probability theory and its applications (Vol. 2). John Wiley & Sons.
Fox, G. E., Baker, N. R., & Bryant, J. L. (1984). Economic models for R and D project selection in the presence of project interactions. Management science,30(7), 890-902.
Friedman, M., & Savage, L. J. (1948). The utility analysis of choices involving risk. The Journal of Political Economy, 279-304.
Gabriel, S. A., Kumar, S., Ordonez, J., & Nasserian, A. (2006). A multiobjective optimization model for project selection with probabilistic considerations. Socio-Economic Planning Sciences, 40(4), 297-313.
Ghorbani, S., & Rabbani, M. (2009). A new multi-objective algorithm for a project selection problem. Advances in Engineering Software, 40(1), 9-14.
Gintis, H. (2009). Game Theory Evolving, 2nd Ed. Princeton University Press, Princeton.
Goldwerger, J. & Paroush, J. (1977). Capital budgeting of interdependent projects: Activity analysis and approach. Management Science, 23 (11), 1242–1246.
Heidenberger, K. & Stummer, C. (1999). Research and development project selection and resource allocation: A review of quantitative modelling approaches. International Journal of Management Reviews, 1 (2), 197–224.
Huang, X. (2007). Optimal project selection with random fuzzy parameters. International Journal of Production Economics, 106, 513–522.
Khanzadi, M., Soufipour, R., & Rostami, M. (2011). A new improved genetic algorithm approach and a competitive heuristic method for large-scale multiple resource-constrained project-scheduling problems. International Journal of Industrial Engineering Computations, 2(4), 737-748.
Kumar, R. & Singh, P.K. (2010). Assessing solution quality of biobjective 0-1 knapsack problem using evolutionary and heuristic algorithms. Applied Soft Computing, 10, 711–718.
Lee, J. W. & Kim, S. H. (2001). An integrated approach for interdependent information system project selection. International Journal of Project Management, 19, 111-118.
Lin, F. (2008). Solving the knapsack problem with imprecise weight coefficients using genetic algorithms. European Journal of Operational Research, 185, 133–145.
Li, Y.F., Xie, M. & Goh, T.N. (2009). A study of project selection and feature weighting for analogy based software cost estimation. Journal of Systems and Software, 82, 241–252.
Liu, B. (2007). Theory and Practice of Uncertain Programming. 2nd ed. Tsinghua University, Beijing.
Medaglia, A. L., Graves, S. B. & Ringuest, J. L. (2007). A multiobjective evolutionary approach for linearly constrained project selection under uncertainty. European Journal of Operational Research, 179, 869–894.
Nemhauser, G.L. & Ullmann, Z. (2013). Discrete dynamic programming and capital allocation. Management Science, 15 (9), 494–505.
Neumann, V., Morgenstern, J. & Morgenstern, O. (1944). Theory of Games and Economic Behavior. Princeton University Press, Princeton.
Rabbani, M., Aramoon Bajestani, M. & Baharian Khoshkhou, G. (2010). A multi-objective particle swarm optimization for project selection problem. Expert Systems with Applications, 37, 315–321.
Santhanam, R. & Kyparisis, G.J. (1996). A decision model for interdependent information system project selection. European Journal of Operational Research, 89, 380–399.
Savage, J. (1954). The Foundations of Statistics. John Wiley & Sons, New York.
Akbari, R., Zeighami, V., & Ziarati, K. (2011). Artificial bee colony for resource constrained project scheduling problem. International Journal of Industrial Engineering Computations, 2(1), 45-60.
Angelelli, E., Mansini, R., & Grazia Speranza, M. (2010). Kernel search: A general heuristic for the multi-dimensional knapsack problem. Computers & Operations Research, 37(11), 2017-2026.
Anscombe, F. J., & Aumann, R. J. (1963). A definition of subjective probability. Annals of mathematical statistics, 34, 199-205.
Birge, J.R. & Louveaux, F. (1997). Introduction to Stochastic Programming. Springer, New York.Charnes, A. & Cooper, W.W. (1959). Chance-constrained programming. Management Science, 6, 73–79.
De, P. K., Acharya, D., & Sahu, K. C. (1982). A chance-constrained goal programming model for capital budgeting. Journal of the Operational Research Society, 33, 635-638.
Fang, Y., Chen, L., & Fukushima, M. (2008). A mixed R & D projects and securities portfolio selection model. European Journal of Operational Research,185(2), 700-715.
Feller, W. (2008). An introduction to probability theory and its applications (Vol. 2). John Wiley & Sons.
Fox, G. E., Baker, N. R., & Bryant, J. L. (1984). Economic models for R and D project selection in the presence of project interactions. Management science,30(7), 890-902.
Friedman, M., & Savage, L. J. (1948). The utility analysis of choices involving risk. The Journal of Political Economy, 279-304.
Gabriel, S. A., Kumar, S., Ordonez, J., & Nasserian, A. (2006). A multiobjective optimization model for project selection with probabilistic considerations. Socio-Economic Planning Sciences, 40(4), 297-313.
Ghorbani, S., & Rabbani, M. (2009). A new multi-objective algorithm for a project selection problem. Advances in Engineering Software, 40(1), 9-14.
Gintis, H. (2009). Game Theory Evolving, 2nd Ed. Princeton University Press, Princeton.
Goldwerger, J. & Paroush, J. (1977). Capital budgeting of interdependent projects: Activity analysis and approach. Management Science, 23 (11), 1242–1246.
Heidenberger, K. & Stummer, C. (1999). Research and development project selection and resource allocation: A review of quantitative modelling approaches. International Journal of Management Reviews, 1 (2), 197–224.
Huang, X. (2007). Optimal project selection with random fuzzy parameters. International Journal of Production Economics, 106, 513–522.
Khanzadi, M., Soufipour, R., & Rostami, M. (2011). A new improved genetic algorithm approach and a competitive heuristic method for large-scale multiple resource-constrained project-scheduling problems. International Journal of Industrial Engineering Computations, 2(4), 737-748.
Kumar, R. & Singh, P.K. (2010). Assessing solution quality of biobjective 0-1 knapsack problem using evolutionary and heuristic algorithms. Applied Soft Computing, 10, 711–718.
Lee, J. W. & Kim, S. H. (2001). An integrated approach for interdependent information system project selection. International Journal of Project Management, 19, 111-118.
Lin, F. (2008). Solving the knapsack problem with imprecise weight coefficients using genetic algorithms. European Journal of Operational Research, 185, 133–145.
Li, Y.F., Xie, M. & Goh, T.N. (2009). A study of project selection and feature weighting for analogy based software cost estimation. Journal of Systems and Software, 82, 241–252.
Liu, B. (2007). Theory and Practice of Uncertain Programming. 2nd ed. Tsinghua University, Beijing.
Medaglia, A. L., Graves, S. B. & Ringuest, J. L. (2007). A multiobjective evolutionary approach for linearly constrained project selection under uncertainty. European Journal of Operational Research, 179, 869–894.
Nemhauser, G.L. & Ullmann, Z. (2013). Discrete dynamic programming and capital allocation. Management Science, 15 (9), 494–505.
Neumann, V., Morgenstern, J. & Morgenstern, O. (1944). Theory of Games and Economic Behavior. Princeton University Press, Princeton.
Rabbani, M., Aramoon Bajestani, M. & Baharian Khoshkhou, G. (2010). A multi-objective particle swarm optimization for project selection problem. Expert Systems with Applications, 37, 315–321.
Santhanam, R. & Kyparisis, G.J. (1996). A decision model for interdependent information system project selection. European Journal of Operational Research, 89, 380–399.
Savage, J. (1954). The Foundations of Statistics. John Wiley & Sons, New York.