ROBUSTNESS MEASURES AND ROBUST SCHEDULING FOR JOB SHOPS

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Abstract
A robust schedule is defined as a schedule that is insensitive to unforeseen shop floor disturbances given an assumed control policy. In this paper, a definition of schedule robustness is developed which comprises two components: post-disturbance make-span and post-disturbance makespan variability. We have developed robustness measures and robust scheduling methods for the case where a “right-shift” control policy is used. On occurrence of a disruption, the right-shift policy maintains the scheduling sequence while delaying the unfinished jobs as much as necessary to accommodate the disruption. An exact measure of schedule robustness is derived for the case in which only a single disruption occurs within the planning horizon. A surrogate measure is developed for the more complex case in which multiple disruptions may occur. This surrogate measure is then embedded in a genetic algorithm to generate robust schedules for job-shops. Experimental results show that robust schedules significantly outperform schedules based on makespan alone.