Evaluating complex military systems and materials offers significant challenges for defense organizations, requiring robust methodologies to assess multiple competing criteria. This study develops and applies an integrated Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution with a dual normalization approach to support armored vehicle acquisition decisions for the Brazilian Army. The research addresses critical gaps in current procurement practices by transforming unstructured technical requirements into machine-readable ReqIF standards and implementing a systematic framework for multi-criteria decision analysis. Through this hybrid AHP-TOPSIS-2N method, the study demonstrates how hierarchical weighting of technical, logistical, and industrial factors can be combined with mathematical ranking of alternatives against ideal solutions. The results identify the optimal vehicle configuration, maintaining consistent top performance across two normalization scenarios. Validation by defense acquisition specialists confirms the effectiveness in enhancing transparency and objectivity in procurement decisions. Beyond military applications, the research contributes to a generalizable decision-support framework adaptable to complex acquisitions across public and private sectors where structured requirements evaluation is paramount.
Fontenelle et al. (Thu,) studied this question.
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