Case Studies

U.S. Army Base Realignment and Closure

Dell, R. F. (1998), Optimizing army base realignment and closure, Interfaces, 28:6, 1-18.

Army Base Realignment and Closure: The United States Army has downsized its forces by more than 30% since 1989. These reductions were accompanied by a detailed plan to eliminate and/or realign dozens of military bases around the world. The closure or realignment of a military base affects the military's ability to deploy personnel and equipment rapidly and also has a major impact on the local economy surrounding the base. Due to the sensitive nature of these decisions and their political impact, Congress passed special legislation governing the decision-making process. A 1995 commission decided to close 29 bases and realign 11 others. Approximately $2 billion was budgeted to implement the decisions with anticipated long-term annual operating savings of $360 million.

A mixed-integer linear programming model was developed to assist the military in scheduling the sequence of closures and realignment over a six-year period while staying within the $2 billion budget. The model's name was BRACAS (Base Realignment and Closure Action Scheduler). The model develops timetables for actions that meet annual budgetary constraints and maximizes the net present value of the plan. 0-1 decision variables were used to represent whether or not in a specific year:

  • a significant number of personnel were removed from a base,
  • construction of a new facility was begun, and
  • all actions related to a specific base were completed.

    During the first application of BRACAS, the schedule it suggested yielded $400 million in savings when compared to the original plan. Major General Robert T. Howard, Deputy Assistant Secretary of the Army for Budget, questioned the results and asked for changes in the assumptions of the model. These model changes were made within an hour and the results were even better than before. This experience was critical in obtaining top-level credibility for BRACAS as a planning tool that could answer a wide range of "what-if" questions. One direct impact of the model was to increase the FY97 allocation by $100 million in order to produce a $233 million dollar savings over the six-year period.

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