A variable neighborhood search simheuristic for project portfolio selection under uncertainty
Panadero, Javier (Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3))
Doering, Jana (Universitat Oberta de Catalunya. Estudis d'Economia i Empresa)
Kizys, Renatas (University of Portsmouth. Portsmouth Business School)
Juan, Ángel A (Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3))
Fitó Bertran, Àngels (Universitat Oberta de Catalunya. Estudis d'Economia i Empresa)

Data:	2020
Descripció:	23 pàg.
Resum:	With limited financial resources, decision-makers in firms 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 flows 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.
Ajuts:	Ministerio de Economía y Competitividad TRA2015-71883-REDT Ministerio de Economía y Competitividad TRA2013-48180-C3-3-P
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Llengua:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Matèria:	Net present value ; Project portfolio selection ; Simheuristics ; Stochastic optimization ; Variable neighborhood search
Publicat a:	Journal of Heuristics, Vol. 26, issue 3 (June 2020) , p. 353-375, ISSN 1572-9397

DOI: 10.1007/s10732-018-9367-z

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