5th International Workshop on Agents Applied in Health Care

Research Article

Support-Based Distributed Optimisation: An Approach to Radiotherapy Scheduling

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  • @INPROCEEDINGS{10.1007/978-3-642-23635-8_41,
        author={Graham Billiau and Chee Chang and Aditya Ghose and Andrew Miller},
        title={Support-Based Distributed Optimisation: An Approach to Radiotherapy Scheduling},
        proceedings={5th International Workshop on Agents Applied in Health Care},
        proceedings_a={A2HC},
        year={2012},
        month={10},
        keywords={},
        doi={10.1007/978-3-642-23635-8_41}
    }
    
  • Graham Billiau
    Chee Chang
    Aditya Ghose
    Andrew Miller
    Year: 2012
    Support-Based Distributed Optimisation: An Approach to Radiotherapy Scheduling
    A2HC
    Springer
    DOI: 10.1007/978-3-642-23635-8_41
Graham Billiau,*, Chee Chang,*, Aditya Ghose,*, Andrew Miller,*
    *Contact email: gdb339@uow.edu.au, c03@uow.edu.au, aditya@uow.edu.au, amiller@uow.edu.au

    Abstract

    The public health system is plagued by inefficient use of resources. Frequently, the results are lengthy patient treatment waiting times. While many solutions for patient scheduling in health systems exist, few address the problem of coordination between independent autonomous departments. In this study, we describe the use of a distributed dynamic constraint optimisation algorithm (Support Based Distributed Optimisation) for the generation and optimisation of schedules across autonomous units. We model the problem of scheduling radiotherapy patients across several independent oncology units as a dynamic distributed constraint optimisation problem. Such an approach minimises the sharing of private information such as department operation details as well as patient privacy information while taking into consideration patient preferences as well as resource utilisation to find a pareto-optimal solution.