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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Costa, A. & Paixão, J. P. (2010). An approximate solution approach for a scenario-based capital budgeting model. Computational Management Science. 7 (3), 337-353
Exportar Referência (IEEE)
A. R. Costa and J. M. Paixão,  "An approximate solution approach for a scenario-based capital budgeting model", in Computational Management Science, vol. 7, no. 3, pp. 337-353, 2010
Exportar BibTeX
@article{costa2010_1732357306491,
	author = "Costa, A. and Paixão, J. P.",
	title = "An approximate solution approach for a scenario-based capital budgeting model",
	journal = "Computational Management Science",
	year = "2010",
	volume = "7",
	number = "3",
	doi = "10.1007/s10287-009-0117-4",
	pages = "337-353",
	url = "http://link.springer.com/article/10.1007%2Fs10287-009-0117-4"
}
Exportar RIS
TY  - JOUR
TI  - An approximate solution approach for a scenario-based capital budgeting model
T2  - Computational Management Science
VL  - 7
IS  - 3
AU  - Costa, A.
AU  - Paixão, J. P.
PY  - 2010
SP  - 337-353
SN  - 1619-697X
DO  - 10.1007/s10287-009-0117-4
UR  - http://link.springer.com/article/10.1007%2Fs10287-009-0117-4
AB  - Real options techniques such as contingent claims analysis and dynamic programming can be used for project evaluation when the project develops stochastically over time and the decision to invest into this project can be postponed. Following that perspective, Meier et al. (Oper Res 49(2):196-2 06, 2001) presented a scenario based model that captures risk uncertainty and managerial flexibility, maximizing the time-varying of a portfolio of investment options. However, the corresponding linear integer program turns out to be quite intractable even for a small number of projects and time periods. In this paper, we propose a heuristic approach based on an alternative scenario based model involving a much less number of variables. The new approach allows the determination of reasonable quality approximate solutions with huge reductions on the computational times required for solving large size instances.
ER  -