Decision support systems (DSS) are valuable tools for information management and decision making guidance, and are vital in decision environments that are inherently dynamic or that leverage a time pressure on the operator. In this work, we detail the application and effectiveness of several decision support techniques in a time-limited decision environment. These techniques, namely heuristic (HIA) and optimal experimental design (OED) information acquisition/restriction, represent heuristic and probabilistic approaches to decision support. In addition to these techniques, participants were given a selection of tasks that allowed free acquisition of information in order to determine their default behavior. Results show that all heuristic and one of the two probabilistic decision support strategies increased accuracy, and that all strategies resulted in faster decision making. Furthermore, free acquisition analysis indicates that participants default to probabilistic strategies even during extended periods of poor performance, which complicates the discussion around "optimal" decision support strategy.