Model Driven Business Transformation --- An Experience Report
BPM '08 Proceedings of the 6th International Conference on Business Process Management
Formal Semantics and Verification of BPMN Transaction and Compensation
APSCC '08 Proceedings of the 2008 IEEE Asia-Pacific Services Computing Conference
Structural Aspects of Business Process Diagram Abstraction
CEC '09 Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing
Business process management: a survey
BPM'03 Proceedings of the 2003 international conference on Business process management
Estimating performance of a business process model
Winter Simulation Conference
On the suitability of BPMN for business process modelling
BPM'06 Proceedings of the 4th international conference on Business Process Management
Automated performance analysis of business processes
Proceedings of the 2012 Symposium on Theory of Modeling and Simulation - DEVS Integrative M&S Symposium
A model-driven method for building distributed simulation systems from business process models
Proceedings of the Winter Simulation Conference
Proceedings of the Symposium on Theory of Modeling & Simulation - DEVS Integrative M&S Symposium
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In this paper we present the problem of optimizing a business process model with the objective of finding the most beneficial assignment of tasks to agents, without modifying the structure of the process itself. The task assignment problem for four types of processes are distinguished and algorithms for finding optimal solutions to them are presented: 1) a business process with a predetermined workflow, for which the optimal solution is conveniently found using the well-known Hungarian algorithm. 2) a Markovian process, for which we present an analytical method that reduces it to the first type. 3) a nonMarkovian process, for which we employ a simulation method to obtain the optimal solution. 4) the most general case, i.e. a nonMarkovian process containing critical tasks. In such processes, depending on the agents that perform critical tasks the workflow of the process may change. We introduce two algorithms for this type of processes. One that finds the optimal solution, but is feasible only when the number of critical tasks is few. The second algorithm is even applicable to large number of critical tasks but provides a near-optimal solution. In the second algorithm a hill-climbing heuristic method is combined with Hungarian algorithm and simulation to find an overall near-optimal solution for assignments of tasks to agents. The results of a series of tests that demonstrate the feasibility of the algorithms are included.