Dynamic Scheduling in Systems with Complex Resource Allocation Requirements

Real world systems can be thought of as structures of activities that require resources in order to execute. Costs are reduced when resource levels are kept low, but this can lead to competition for resources that can cause poor system performance. Careful allocation of resources can improve system performance by enabling more efficient use of resources. This paper proposes that resource scheduling be done in a series of dynamic reschedulings that use precise and detailed information about the system and available resources to improve the quality of scheduling results. Each rescheduling is done over a relatively small set of activities, and a genetic algorithm is used to support scheduling computations. Simulations of healthcare systems are used to evaluate this approach. Results indicate that this approach can support effective dynamic rescheduling at affordable costs.