Improved bounds on relaxations of a parallel machine scheduling problem

被引:15
|
作者
Phillips, CA
Schulz, AS
Shmoys, DB
Stein, C
Wein, J
机构
[1] Sandia Natl Labs, Albuquerque, NM 87185 USA
[2] Tech Univ Berlin, Dept Math, D-1000 Berlin, Germany
[3] Cornell Univ, Sch Operat Res & Ind Engn, Ithaca, NY 14853 USA
[4] Cornell Univ, Dept Comp Sci, Ithaca, NY 14853 USA
[5] Dartmouth Coll, Dept Comp Sci, Sudikoff Lab, Hanover, NH 03755 USA
[6] Polytech Univ, Dept Comp Sci, Brooklyn, NY 11201 USA
基金
美国国家科学基金会;
关键词
scheduling; preemptive scheduling; release dates; identical parallel machines; average completion time; approximation algorithms; relaxations; linear programming;
D O I
10.1023/A:1009750913529
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We consider the problem of scheduling n jobs with release dates on m identical parallel machines to minimize the average completion time of the jobs. We prove that the ratio of the average completion time of the optimal nonpreemptive schedule to that of the optimal preemptive schedule is at most 7/3, improving a bound of (3 - 1/m) due to Phillips, Stein and Wein. We then use our technique to give an improved bound on the quality of a linear programming relaxation of the problem considered by Hall, Schulz, Shmoys and Wein.
引用
收藏
页码:413 / 426
页数:14
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