A two-stage sustainable uncertain multi-objective portfolio selection and scheduling considering conflicting criteria
This article presents a pioneering approach to project portfolio selection and scheduling, addressing the complexities of contemporary decision-making environments characterized by uncertainty, conflicting criteria, and sustainability imperatives. The proposed framework integrates multiple-attribute...
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| Published in: | Engineering applications of artificial intelligence Vol. 132; p. 107942 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01-06-2024
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | This article presents a pioneering approach to project portfolio selection and scheduling, addressing the complexities of contemporary decision-making environments characterized by uncertainty, conflicting criteria, and sustainability imperatives. The proposed framework integrates multiple-attribute and multiple-objective decision-making methods, offering a two-stage solution incorporating fuzzy-robust-stochastic (FRS) optimization techniques. Notably, our work introduces a novel heuristics algorithm designed to optimize conflicting criteria related to sustainability, time-dependency, resources, budget constraints, and human resource capabilities. In the first stage, the framework employs advanced multiple-attribute decision-making methods to comprehensively evaluate project portfolios under the influence of diverse and conflicting criteria. Subsequently, the second stage employs sophisticated multiple-objective decision-making methods to refine the portfolio selection by considering fuzzy, robust, and stochastic optimization elements. The introduced heuristics algorithm plays a pivotal role in enhancing the efficiency and effectiveness of the decision-making process, providing a robust solution to the intricate challenges posed by sustainability concerns, temporal dependencies, resource constraints, budget limitations, and human resource capabilities. The innovation lies in the integration of these disparate elements into a cohesive, two-stage framework, which not only ensures the optimal selection of portfolios but also holistically addresses the intricacies of scheduling. Applying FRS optimization in tandem with the novel heuristics algorithm sets this work apart, offering a versatile and comprehensive solution to decision-makers facing the multifaceted challenges of contemporary project management. Finally, different sensitivity analyses on the proposed model and evaluations of the solution algorithm in various test problems highlight the flexibility of the model against uncertainty and optimality of our solutions to address the given complex criteria. The results showed that more benefits could be obtained by dividing the projects. Despite the increase in total profit, it can increase the risks associated with the completion of the project. In addition, the scheduling of unallocated projects in some periods faces limited resources. On the other hand, sensitivity analysis on Robustness and penalty costs showed that the FRS model could cover the weaknesses of the proposed model in the deterministic model.
•Novel methodology for enhanced portfolio selection and scheduling.•Specialization in optimizing two-stage stochastic model.•Applying heuristics approaches for complex sustainable portfolio selection.•Integrating conflicting criteria with hybrid uncertainty. |
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| ISSN: | 0952-1976 |
| DOI: | 10.1016/j.engappai.2024.107942 |