MARKING OPTIMIZATION OF STOCHASTIC TIMED EVENT GRAPHS USING IPA

This paper addresses the marking optimization of stochastic timed even t graphs, where the transition firing times are generated by random va riables with general distributions. The marking optimization problem c onsists of obtaining a given cycle time while minimizing a p-invariant criterion. We propose two heuristic algorithms, both starting from th e optimal solution to the associated deterministic problem and iterati vely adding tokens to adequate places as long as the given cycle time is not obtained. Infinitesimal perturbation analysis of the average cy cle time with respect to the transition firing times is used to identi fy the appropriate places in which new tokens are added at each iterat ion. Numerical results show that the heuristic algorithms provide solu tions better than the ones obtained by the existing methods.