Abstract
System-of-systems (SoS) warfare has become the main form of modern warfare, where various equipment interact and interconnect to achieve operational goals. The complexity of equipment SoS poses a challenge for evaluating equipment under such warfare environments, as it requires considering multiple elements such as tasks and capabilities to ensure reliable evaluations. This paper proposes a novel equipment evaluation approach for SoS warfare environments based on the intuitionistic fuzzy weighted influence non-linear gauge system (IF-WINGS). The approach employs intuitionistic fuzzy sets (IFS) to represent uncertain information related to tasks, capabilities, and equipment. By extending the WINGS method with IFS, the proposed approach uncovers the interdependencies among the elements within the equipment SoS using the causal relation graph, considering both the strength and influence intensity of these elements. Additionally, the proposed approach evaluates and ranks different alternatives using relative closeness, which takes into account the distance of each alternative from the best and worst solutions, and this enables a more reliable and effective evaluation of alternatives. A novel equipment evaluation approach that considers the interrelationships among various elements within the equipment SoS is introduced based on IF-WINGS. To demonstrate the effectiveness of the proposed method, a case study is presented, and the results are compared to other methods, with Spearman’s rank correlation coefficients of the comparative methods obtained as (0.96,0.96,1.00,1.00), respectively. The results show that the proposed method could provide reliable and robust results for equipment evaluation in SoS warfare environments. By introducing the IF-WINGS method into equipment evaluation under SoS environment, this study provides a novel and effective way that considers the complex relationships among different elements in SoS warfare, enabling reliable and reasonable evaluation. In conclusion, the IF-WINGS method proves to be a valuable tool for assessing equipment performance in complex and interconnected warfare scenarios.
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