Sustainable Project Portfolio Selection Considering Combined Rankings Under Uncertainty: A Case Study

Document Type : Research Paper

Authors

1 Department of Industrial Engineering, Yazd University, Iran

2 Department of industrial engineering, Yazd University, Yazd, Iran

10.22059/aie.2023.358307.1866

Abstract

Due to resource limitations such as time, money, and human forces, project-oriented organizations always decide to choose among their candidate projects. In sustainable decision-making, in addition to responding to the internal needs of the organization, responding to social needs and protecting the environment are also taken into consideration. More specifically, in sustainable project selection, projects are selected with a wider view including economic, social, and environmental pillars. In this article, a combined approach has been presented to select investment projects sustainably, determining the ranking of projects based on the combined output of several multi-attribute decision-making methods. Since the data needed in decision-making is often associated with uncertainty, the problem of project selection has been modeled and analyzed in a non-deterministic way using a robust optimization approach. In the studied case, six projects were selected by the deterministic model, while the robust model reduced them to three projects due to the pessimistic modeling approach. It was also observed that by taking into account the uncertainty, the optimal values of three objective functions have been reduced by 28%, 46%, and 28% respectively; but the validity of the answers is guaranteed in non-deterministic real-world situations, which is very important in the investment problems. The main benefits of the proposed approach are: 1) integrating evaluation and selection phases in order to make wise and optimal decisions, 2) combining the results of different MCDM methods which helps the managers with selecting the projects that are generally acceptable by MCDM methods, 3) because a robust optimization model is implemented, the model solutions remain more feasible in resource fluctuations, and 4) the model prevents ignoring high-priority projects which can be outranked by permutations of lower-priority projects.

Keywords

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References

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Advances in Industrial Engineering
Volume 57, Issue 2
December 2023
Pages 187-201

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