DOI: 10.1177/15485129251326915 ISSN: 1548-5129

Strategic modeling innovations: enhancing military decision-making through advanced entropy-based multi-criteria analysis and comprehensive evaluation

Sideris Kiratsoudis, Vasileios Tsiantos

The military decision-making process (MDMP) stands as a cornerstone of military operations, offering a structured framework for evaluating complex tactical scenarios and devising optimal courses of action (COAs) to achieve military objectives. Conventionally, the MDMP heavily relies on manual decision-making methods, drawing upon the expertise and experience of military personnel. However, while several multi-attribute decision-making (MADM) models have been developed to support aspects of the MDMP, they often fall short in adequately addressing decision criteria and fail to consider the overall stability of the process. This research paper presents a comprehensive examination of the MDMP by introducing a novel application of an entropy-based MADM method. This innovative approach offers a systematic treatment of the MDMP, emphasizing the importance of decision criteria and providing a means to quantify their significance. Moreover, the method enables the assessment of the overall stability of the MDMP, a critical aspect often overlooked in existing models. Through a rigorous case study and sensitivity analysis, the effectiveness of the proposed model is validated, demonstrating its capacity to enhance the MDMP. By integrating advanced computational techniques, the model facilitates the generation of prompt, accurate, and resilient solutions, thereby addressing key challenges faced in traditional MDMPs. The utilization of an entropy-based MADM method represents a significant advancement in military decision-making, offering a more comprehensive and analytically rigorous approach to evaluating and optimizing COAs within the MDMP framework. This research contributes to the ongoing efforts to modernize MDMPs, ultimately enhancing the effectiveness and efficiency of military operations in complex and dynamic environments.

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