1810. An Analysis of the SAPEVO-PC-WASPAS Hybrid Multicriteria Method in the Selection of Virtual Reality Glasses for Applications at the Center for Naval Systems Analysis
Invited abstract in session WA-8: Decision aiding under uncertainty 1, stream Multiple Criteria Decision Aiding.
Wednesday, 8:30-10:00Room: Clarendon SR 2.08
Authors (first author is the speaker)
| 1. | Thaís Evelin Santos de Oliveira
|
| Center for Naval Systems Analyses (CASNAV), Fluminense Federal University (UFF) | |
| 2. | Gilson Brito Alves Lima
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| Production Engineering, Universidade Federal Fluminense | |
| 3. | Marcos Santos
|
| Industrial Engineering, Fluminense Federal University | |
| 4. | Igor Pinheiro de Araujo Costa
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| Production Engineering, Center for Naval Systems Analyses (CASNAV) / Fluminense Federal University (UFF) | |
| 5. | Giovanna Moura
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| CCJ, Centro Universitário de João Pessoa | |
| 6. | DANIEL PEREIRA
|
| UAEP, Federal University of Campina Grande | |
| 7. | Gabriel Custódio Rangel
|
| Operational Research , Naval Systems Analysis Center |
Abstract
The rapid advancement of virtual reality (VR) technology has transformed various industries, especially training and simulation. Selecting the most suitable VR glasses for specific applications is complex due to multiple technical and operational criteria. This study tackles this challenge using a hybrid multi-criteria decision-making (MCDM) approach, combining SAPEVO-PC and WASPAS methodologies to optimize VR glasses selection for the Center for Naval Systems Analysis (CASNAV), a key institution in the Brazilian Navy focused on simulation-based training.
The proposed methodology structures decision-making through expert evaluations and multi-criteria analysis, ensuring transparency and consistency while balancing qualitative and quantitative factors. It identifies and prioritizes VR glasses that align with CASNAV’s operational needs, considering software compatibility, resolution, field of view, weight, connectivity, and cost.
This research holds academic and practical significance. Academically, it advances hybrid MCDM applications in complex decision-making. Practically, it enhances VR-based military training by reducing costs, improving efficiency, and optimizing immersive learning. The proposed approach is adaptable to other strategic environments, reinforcing its broader applicability in selecting advanced technologies.
Keywords
- Decision Support Systems
- Multi-Objective Decision Making
Status: accepted
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