Title: An integrated model for evaluation and optimisation of business project portfolios

Authors: Maria Auxiliadora Cannarozzo Tinoco; Camila Costa Dutra; José Luis Duarte Ribeiro; Rogério Feroldi Miorando; Carla Schwengber Ten Caten

Addresses: Department of Industrial and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil ' Department of Industrial and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil ' Department of Industrial and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil ' Department of Engineering and Production Systems, Universidade Federal de Santa Catarina, Florianópolis, Brazil ' Department of Industrial and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

Abstract: This paper presents an integrated model for the evaluation and probabilistic optimisation of project portfolios, integrating economic, social and environmental impacts analysis. The contribution of the proposed model lies in: 1) an extended list of criteria covering economic, social and environmental aspects; 2) use of financial measures, which are easily understood; 3) use of Monte Carlo simulation to cope with variability; 4) use of mathematical optimisation to deal with constraints and/or large amount of information. A practical test carried out in a company is reported and confirms the applicability and usefulness of the model. The integration of approaches for sustainable assessment of business projects and selection and optimisation of project portfolio is deficient in literature. Thereby, the proposed model is presented as an alternative to conduct integrated analysis and define optimal project portfolio for sustainable development in business contexts characterised by uncertainties. [Received: 26 October 2015; Revised: 26 August 2017; Revised: 1 March 2018; Accepted: 1 March 2018]

Keywords: project portfolio selection; economic analysis; social and environmental impact analysis; probabilistic optimisation.

DOI: 10.1504/EJIE.2018.092010

European Journal of Industrial Engineering, 2018 Vol.12 No.3, pp.442 - 463

Published online: 24 May 2018 *

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