A game-theoretic control approach for job shops in the presence of disruptions

A methodology inspired by a game-theoretic view of the on-line control problem for job-shops is developed which allows the use of static off-line schedules in uncertain environments, and the explicit incorporation of deterministic and stochastic information concerning future disturbances. A discrete event dynamic system representation is used to formulate the control problem. The control objectives are to minimize expected makespan and deviations from an off-line schedule. Computational tractability is achieved through a graph-theoretic decomposition of the job-shop scheduling problem, the development of fast rescheduling heuristics, and efficient sampling of future events. A heuristic search algorithm is developed for problem resolution. Experimental results show that the methodology significantly outperforms existing control methods such as ‘total rescheduling’ and ‘right-shift.’ Most importantly, the control methodology demonstrates consistent performance and small CPU time requirements throughout the tests.