The traditional focus of scheduling research is on finding schedules with a low implementation cost. However, in many real world scheduling applications finding a robust or flexible schedule is just as important. A robust schedule is a quality schedule expected to still be acceptable if something unforeseen happens, while a flexible schedule is a quality schedule expected to be easy to change. In this paper, the robustness and flexibility of schedules produced by minimising different robustness measures are investigated. One kind of robustness measure is the neighbourhood-based robustness measure, in which the basic idea is to minimise the implementation costs of a set of schedules located around a centre schedule. For tardiness problems another way of improving robustness is to increase the slack of the schedule by minimising lateness instead of tardiness. The problems used in the experiments are maximum tardiness, summed tardiness and total flow-time job shop problems. The experiments showed that the neighbourhood-based robustness measures improves robustness for all the problem types. Flexibility is improved for maximum tardiness and loose summed tardiness problems, while it is not improved for tight summed tardiness problems and total flow-time problems. The lateness-based robustness measures are found to also improve robustness and in some cases flexibility for the same problems, but the improvement is not as substantial as with the neighbourhood-based measures. Based on these observations, it is conjectured that neighbourhood-based robustness can be expected to improve flexibility on problems with few critical points.
In REF , a "neighborhood-based" measure of robustness is defined for a job-shop environment.
Improving Robustness and Flexibility of Tardiness and Total Flowtime Job Shops Using Robustness Measures
Journal of Applied Soft Computing
Mathematics Computer Science