NDLI: The interval perturbation robustness of an optimal schedule for single machine discounted total weighted completion time problem

Content Provider	IEEE Xplore Digital Library
Author	Li Jiangeng Ruan Xiaogang Yang Ming
Copyright Year	2004
Description	Author affiliation: Sch. of Electr. Inf. & Control Eng., Beijing Univ. of Technol., China (Li Jiangeng; Ruan Xiaogang)
Abstract	The robustness of a schedule is an important problem in practice. In this paper it is studied in the angle that the optimal schedules do not change. Firstly, the interval perturbation robustness of an optimal schedule is defined, that is the property that an optimal schedule keeps the same when some of the parameters in the scheduling problem vary in some intervals. Then the interval perturbation robustness of an optimal schedule for single machine discounted total weighted completion time is studied. Form a lemma that gives the relationship between the order of r parameters and the overlaps between each two of the intervals in which these parameters vary, the results in this paper are proved. The results are three if and only if conditions under which an optimal schedule is of interval perturbation robustness. These results relate to the optimality of a schedule at some of the vertices of a hyperrectangle of r dimension consisting of the varying parameters. Some examples that show how to use these results are given.
Sponsorship	Zhejian Univ. Nat. Lab. of Ind. Control Technol. IEEE Robotics and Automation Soc. Nat. Natural Sci. Found. of China Chinese Assoc. of Automation
Starting Page	2885
Ending Page	2888
File Size	198269
Page Count	4
File Format	PDF
ISBN	0780382730
DOI	10.1109/WCICA.2004.1343042
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Optimal scheduling Single machine scheduling Control engineering Robotics and automation Robust control
Content Type	Text
Resource Type	Article

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