Title :
Asymptotic performance ratio of an online algorithm for the single machine scheduling with release dates
Author :
Chou, Cheng-Feng Mabel
Author_Institution :
Dept. of Decision Sci., Nat. Univ. of Singapore, Singapore
fDate :
5/1/2004 12:00:00 AM
Abstract :
We analyze the single machine weighted completion time problem with release dates and prove that the asymptotic performance ratio of a simple online algorithm is one. This implies that this algorithm generates a solution whose relative error decreases to zero as the number of jobs increases. Our proof does not require any probabilistic assumption on the job parameters and relies heavily on properties of optimal solutions to a linear programming relaxation of the problem.
Keywords :
linear programming; probability; single machine scheduling; asymptotic performance ratio; job parameters; linear programming relaxation; online algorithm; release dates; single machine scheduling; single machine weighted completion time problems; Algorithm design and analysis; Approximation algorithms; Linear programming; Mathematical programming; Optimal scheduling; Performance analysis; Scheduling algorithm; Single machine scheduling; Algorithms; mathematical programming; scheduling;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2004.825984