Optimization of the future soldier system: An integrative approach based on an agent-based simulation and response surface method

With the rise of the future soldier system, an increase in equipment performance of an individual soldier denotes not simply an increase of individual performance but an increase of combat unit performance. Since a soldier's performance depends on a variety of equipment, determining its optimal value is a critical problem. Despite the gravity of the situation, the literature on optimizing future soldier system performance is surprisingly sparse. The difficulties of conducting real tests and evaluations compound the problem. To address these limitations, we use a hybrid approach that combines an agent-based simulation and the Response Surface Methodology (RSM) to optimize the performance of future soldier system. Using an agent-based simulation to address this military problem is practical for two reasons. First, each soldier can be considered an independent agent who acts according to rules. Second, these agents interact closely with other soldiers or their operational environment. Using an agent-based simulation to collect system response estimates, a surrogate function of the system is identified, used as an objective function in an optimization and an optimal system setting is estimated.