Combining simulation and optimization to solve the multimachine interference problem

Optimal allocation of operations to automated ma chines becomes more complex if the labor force or the machinery is heterogeneous. The stochastic nature of the system must also be considered. Thus the problem is a stochastic, integer, nonlinear con strained-optimization problem. We solve it by con structing a simulation model of the operator/machine system and optimizing the simulator using several direct-search methods. The results provide optimal or near-optimal strategies for assigning operators of different skill levels to multiple classes of machines under constraints of operator availability.