Abstract
Resource allocation could be one of the great challenges in business process management. Although there is much research on this subject, task similarities have been paid little attention. In this paper, a new approach is proposed for resource allocation to optimize cycle time by minimizing entropy of work list while keeping workloads balanced. The idea of the entropy of work list comes from the fact that the time it takes for a resource to do similar tasks in a rather consecutive order is less than the time it takes to do the same tasks in a sporadic manner. To this end, an entropy measure is defined, which represents task similarities on some work list. Furthermore, workload balancing is regarded as an objective because not only is cycle time reduction important, but workload fairness should also be met. Experimental results on a real-life event log of BPI challenge 2012 show that the proposed method leads the reduction in cycle time, compared to some other well-known algorithms.
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