Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/3878
Title: An Asymptotically Optimal On-Line Algorithm for Parallel Machine Scheduling
Keywords: Weighted Shortest Processing Requirement on-line heuristic
job processing requirements and weights
Issue Date: 9-Oct-2013
Description: Jobs arriving over time must be non-preemptively processed on one of m parallel machines, each of which running at its own speed, so as to minimize a weighted sum of the job completion times. In this on-line environment, the processing requirement and weight of a job are not known before the job arrives. The Weighted Shortest Processing Requirement (WSPR) on-line heuristic is a simple extension of the well known WSPT heuristic, which is optimal for the single machine problem without release dates. We prove that the WSPR heuristic is asymptotically optimal for all instances with bounded job processing requirements and weights. This implies that the WSPR algorithm generates a solution whose relative error approaches zero as the number of jobs increases. Our proof does not require any probabilistic assumption on the job parameters and relies extensively on properties of optimal solutions to a single machine relaxation of the problem.
Singapore-MIT Alliance (SMA)
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: http://hdl.handle.net/1721.1/3878
Appears in Collections:MIT Items

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.