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These troublesome jobs present a risk to the manufacturing process and to the schedule robustness.
To that aim, we introduce the concept of schedule robustness and we develop a bi-objective resource-constrained project scheduling model.
A measure of schedule robustness based on qualitative possibility theory is proposed to guide the search process to determine the robust schedule; i.e., the schedule with the best worst-case performance.
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In this paper, the design and development of fuzzy scheduled robustness, tracking, disturbance rejection and overall aggressiveness (RTDA) controller design for non-linear processes are discussed.
The proposed approach is based on a design procedure consisting in casting gain-scheduling and robustness requirements into the framework of structured H∞ design.
Further, a gain-scheduling approach and a robustness enhancement are introduced, leading to a robust gain-scheduling observer.
It is found that the reliability and robustness of schedule implementation is significantly improved after optimisation.
Afterwards the cost function is used in conjunction with a genetic algorithm to find an optimized schedule that maximizes its robustness.
Forecast errors exert inevitable disturbance on the robustness of scheduling strategy.
In addition, how to measure the robustness of scheduling heuristics (when they are applied to different/unseen scenarios) is still a open research question.
Therefore, in this paper, in addition to comparing the system throughput under different policies, we introduce the notion of robustness of scheduling policies.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com