On Line Maintenance of Optimal Schedules for a Single Machine
On Line Maintenance of Optimal Schedules for a Single Machine
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We denote the maximum subadditive penalty as f^ax- ^^^ section studies the competitiveness of on-line reoptimLzation, with and without preemption, when all jobs have consistent, subadditive penalty functions. When preemptions are permitted, we show that the on-line reoptimization strategy is 2-competitive, i. E. , the objective value of the on-line schedule is at most twice the optimal off-line value. When preemption is prohibited, the worst-case ratio increases to (p+2), where p is a specified... ratio of job processing times.
5. 1. 1 Scheduling with Preemptions We now show that, for any k-job problem, the preemptive schedule obtained using on-line reoptimization (without anticipating future job arrivals) has a worst-case performance ratio of 2 relative to the optimal off- line schedule for the l/r^ prec, pmtn/f^^^ problem constructed by the enhanced Forward algorithm (Appendix 1).
Theorem 1: For the 1/prec, r^ pmtn/f^^^ problem, on-line reoptimization is 2- competitive.
-17- Proof: Let n be the preemptive schedule obtained using on-line reoptiniization for a k-job problem.
What to read after On Line Maintenance of Optimal Schedules for a Single Machine?
You can find similar books in the "Read Also" column, or choose other free books by Amril Aman to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
We denote the maximum subadditive penalty as f^ax- ^^^ section studies the competitiveness of on-line reoptimLzation, with and without preemption, when all jobs have consistent, subadditive penalty functions. When preemptions are permitted, we show that the on-line reoptimization strategy is 2-competitive, i. E. , the objective value of the on-line schedule is at most twice the optimal off-line value. When preemption is prohibited, the worst-case ratio increases to (p+2), where p is a specified... ratio of job processing times.
5. 1. 1 Scheduling with Preemptions We now show that, for any k-job problem, the preemptive schedule obtained using on-line reoptimization (without anticipating future job arrivals) has a worst-case performance ratio of 2 relative to the optimal off- line schedule for the l/r^ prec, pmtn/f^^^ problem constructed by the enhanced Forward algorithm (Appendix 1).
Theorem 1: For the 1/prec, r^ pmtn/f^^^ problem, on-line reoptimization is 2- competitive.
-17- Proof: Let n be the preemptive schedule obtained using on-line reoptiniization for a k-job problem.
What to read after On Line Maintenance of Optimal Schedules for a Single Machine?
You can find similar books in the "Read Also" column, or choose other free books by Amril Aman to read onlineMoreLess
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