Fuzzy Multiple Criteria Base Realignment and Closure (BRAC) Benchmarking System at the Department of Defense

Purpose: The United States Government adopted the Base Realignment and Closure (BRAC) to resolve the military, economic and political issue of excess base capacity. There have been five rounds of BRAC since 1988, and more are expected to come in the years ahead. The complexity of the closure and realignment decisions and the plethora of factors that are often involved necessitate the need for a sound theoretical framework to structure and model the decision-making process. Design/methodology/approach: We present a multiple criteria benchmarking system that integrates the employment, environmental, financial, strategic and tactical impacts of the closure and realignment decisions into a weighted-sum measure called the "survivability index." The proposed index is used to determine whether the returns generated by each military base on the Department of Defense (DoD) hit list meet a sufficient target benchmark. Findings: There is a significant amount of evidence that intuitive decision-making is far from optimal and it deteriorates exponentially with problem complexity. The benchmarking system presented in this study helps decision makers (DMs) crystallize their thoughts and reduce the environmental complexities inherent in the base realignment and closure decisions. Our model is intended to create an even playing field for benchmarking and pursuing consensus not to imply a deterministic approach to BRAC decisions. Originality/Value: An iterative process is used to consistently analyze the objective and subjective judgments of multiple DMs within a structured framework based on the analytic network process (ANP) and fuzzy logic. This iterative and interactive preference modeling procedure is the basic distinguishing feature of our model as opposed to statistical and optimization decision-making approaches