OptiMAM is a research project on the optimisation of model-driven service design based on stochastic analysis methods. The OptiMAM project focuses on the definition of novel algorithms to enable the optimisation of service-oriented architecture design and business
process management. The project has a modelling scope and wants to deliver better methods for evaluating and optimising the design of workflows underpinning service-oriented architectures and business processes.

Research objectives of this project are therefore to:

1. develop model-to-model transformations from BPMN
   into layered queueing networks (LQNs) that can ex-
   ploit the specic features of matrix-analytic methods
   (MAM);
2. to accurately and eciently evaluate BPMN models,
   dening novel LQN analysis algorithms based on de-
   composition methods and MAM;
3. develop a case study on work ow optimisation with our
   partner BOC, validating our algorithms on real-world
   BPMN instances;
4. integrate the developed and validated algorithms in
   Line, our open source LQN solver.