Scheduling and optimization for a class of single-stage hybrid manufacturing systems

A study on modeling, scheduling and optimal control problems for a class of hybrid manufacturing systems is investigated. In this framework, the discrete entities have a state characterized by a temporal component whose evolution is described by event-driven dynamics and a physical component whose evolution is described by continuous time-driven dynamics, thus it is a typical hybrid system. Not only the optimal control for manufacturing processes like that discussed in many references but also the optimal machining sequence are considered. The whole problem is solved by a two-level optimization method: in the inner level, for any given machining sequence of the jobs, the optimal control for the manufacturing process is considered, which is a nonsmooth, nonconvex optimization problem in the general case; while at the outer level, we use an improved genetic algorithm to decide the optimal machining sequence of a batch of jobs to be processed. Finally, some examples are given to illustrate the validity of our algorithm.