Intelligent Scheduling in Complex Dynamic Distributed Environments

The complexity and changeability of interacting factors affecting scheduling in a distributed environment demands a very flexible and dynamic solution, in order to achieve a high level of utilisation and cater for many different competing priorities. A typical example of the problem domain can be found in elective surgery scheduling where efficient scheduling is critical to ensure optimum utilisation of the public health system. Current approaches have however failed to offer an efficient solution. The task of making complex resource allocation decisions is still left up to the operators of the system. We propose a multi-agent approach to modelling distributed environments that employs distributed constraint satisfaction for intelligent scheduling. The proposed model is based on a case study of elective surgery scheduling at the Princess Alexandra Hospital in Brisbane, Australia.