List's worst-average-case or WAC ratio

Authors:
Christopher J. Osborn;Eric Torng
Affiliations:
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, USA 61801;Department of Computer Science and Engineering, Michigan State University, East Lansing, USA 48824
Venue:
Journal of Scheduling
Year:
2008

Citing 9
Cited 0

On the performance of on-line algorithms for partition problems

Acta Cybernetica
An on-line scheduling heuristic with better worst case ratio than Graham's list scheduling

SIAM Journal on Computing
A better lower bound for on-line scheduling

Information Processing Letters
New algorithms for an ancient scheduling problem

Journal of Computer and System Sciences - Special issue on selected papers presented at the 24th annual ACM symposium on the theory of computing (STOC '92)
A better algorithm for an ancient scheduling problem

Journal of Algorithms
Best-fit bin-packing with random order

Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
Better Bounds for Online Scheduling

SIAM Journal on Computing
Generating adversaries for request-answer games

SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Improved Bounds for the Online Scheduling Problem

SIAM Journal on Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We analyze the List scheduling algorithm for the problem of minimizing makespan using a worst-average-case or wac analysis technique, previously used by Kenyon for analyzing the Best Fit bin packing algorithm. We show that List's worst-average-case or wac ratio asymptotically approaches 2, as m-∞. Thus, List's worst-case behavior is not overly dependent on the order of job arrivals.