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http://hdl.handle.net/10609/113486
Title: A variable neighborhood search simheuristic for project portfolio selection under uncertainty
Author: Panadero Martínez, Javier  
Doering, Jana
Kizys, Renatas
Juan Pérez, Ángel Alejandro
Fitó Bertran, Àngels
Others: University of Portsmouth
Universitat Oberta de Catalunya (UOC)
Keywords: project portfolio selection
stochastic optimization
net present value
variable neighborhood search
simheuristics
Issue Date: 14-Feb-2018
Publisher: Journal of Heuristics
Citation: Panadero, J., Doering, J., Kizys, R., Juan, A.A. & Fitó Bertran, A. (2020). A variable neighborhood search simheuristic for project portfolio selection under uncertainty. Journal of Heuristics, 26, 353-375. doi: 10.1007/s10732-018-9367-z
Project identifier: info:eu-repo/grantAgreement/TRA2013-48180-C3-P
info:eu-repo/grantAgreement/TRA2015-71883-REDT
info:eu-repo/grantAgreement/20161ES01KA108023465
Also see: https://link.springer.com/article/10.1007/s10732-018-9367-z
Abstract: With limited nancial resources, decision-makers in rms and governments face the task of selecting the best portfolio of projects to invest in. As the pool of project proposals increases and more realistic constraints are considered, the problem becomes NP-hard. Thus, metaheuristics have been employed for solving large instances of the project portfolio selection problem (PPSP). However, most of the existing works do not account for uncertainty. This paper contributes to close this gap by analyzing a stochastic version of the PPSP: the goal is to maximize the expected net present value of the inversion, while considering random cash ows and discount rates in future periods, as well as a rich set of constraints including the maximum risk allowed. To solve this stochastic PPSP, a simulation-optimization algorithm is introduced. Our approach integrates a variable neighborhood search metaheuristic with Monte Carlo simulation. A series of computational experiments contribute to validate our approach and illustrate how the solutions vary as the level of uncertainty increases.
Language: English
URI: http://hdl.handle.net/10609/113486
ISSN: 1381-1231MIAR
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