This paper describes a heuristic which produces efficient makespans for resource-constrained scheduling problems with parallel processing capabilities. This heuristic was initially developed for the scheduling of army battalion training exercises. The original heuristic has also been successfully applied to solve problems in project scheduling with limited resources, generalized job shop scheduling, and resource-constrained scheduling. The exchange heuristic requires an initial feasible solution upon which it improves the makespan by efficiently and systematically shuffling activities while maintaining feasibility. The method has recently been modified twice, termed the intelligent version and naive version, respectively, such that its ability to reduce the initial makespan is enhanced. In this study, it is shown that the heuristic, in both the modified intelligent version and original version, can be applied to resource-constrained scheduling problems with processing The performance of the intelligent version is compared to the original version in four different resource-constrained (parallel processing) problems of varied complexity. Results show that the modified heuristic produces significantly better makespans than the original heuristic when sufficient numbers of activities are involved in each precedence relationship. However there is a cost of increased CPU time associated with the improved makespan performance.