Decisions about allocating resources in health care are complex, and their undertaking requires the use of sophisticated models and methods. The generalized allocation model is based on assigning a group of tasks to a series of resources with a minimum total cost to the system.

Each resource is limited and each task must be assigned to a single resource. This model has numerous applications in health care, especially in corrective allocations and in those dealing with certain equipment or material. A proper allocation can significantly reduce costs within the health care system.

The solution to this type of problem is presented via an adaptive heuristic based on the GRASP (Greedy Randomized Adaptive Search Heuristic) and MMAS (MAX-MIN Ant System) systems. This method has the advantage of adapting easily to new restrictions or conditions arising from the problem. The paper concludes with computational results that prove that this method is among the most efficient of those known today, as well as final observations.