Semi-on-line scheduling with ordinal data on two uniform machines

Authors:
Zhiyi Tan;Yong He
Affiliations:
Department of Mathematics, Zhejiang University, Hangzhou 310027, People's Republic of China;Department of Mathematics, Zhejiang University, Hangzhou 310027, People's Republic of China
Venue:
Operations Research Letters
Year:
2001

Citing 7
Cited 8

Amortized efficiency of list update and paging rules

Communications of the ACM
Semi on-line scheduling on two identical machines

Computing
Randomized online scheduling on two uniform machines

Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
On-Line Bin-Stretching

RANDOM '98 Proceedings of the Second International Workshop on Randomization and Approximation Techniques in Computer Science
Semi on-line algorithms for the partition problem

Operations Research Letters
Ordinal algorithms for parallel machine scheduling

Operations Research Letters
Bin packing using semi-ordinal data

Operations Research Letters

Semi-online scheduling with machine cost

Journal of Computer Science and Technology
Optimal on-line algorithms for the uniform machine scheduling problem with ordinal data

Information and Computation
Semi-online algorithms for parallel machine scheduling problems

Computing
Optimal semi-online preemptive algorithms for machine covering on two uniform machines

Theoretical Computer Science
Semi-online scheduling jobs with tightly-grouped processing times on three identical machines

Discrete Applied Mathematics - Special issue: Max-algebra
Semi-online scheduling jobs with tightly-grouped processing times on three identical machines

Discrete Applied Mathematics
Optimal on-line algorithms for the uniform machine scheduling problem with ordinal data

Information and Computation
Semi-on-line problems on two identical machines with combined partial information

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

We investigate the problem of semi-on-line scheduling of jobs on two uniform machines where the order of jobs by their processing times is known as a priori. We propose an algorithm for any machine speed ratio s=1. We also present a comprehensive lower bound, which is a piecewise function of s. The algorithm is optimal for the majority of s@?[1,~). The total length of the intervals of s where the competitive ratio does not match the lower bound is less than 0.7784 and the biggest gap between them never exceeds 0.0521.