Scheduling orders on either dedicated or flexible machines in parallel to minimize total weighted completion time
Document Type
Article
Publication Date
3-1-2008
Abstract
We are interested in the problem of scheduling orders for different product types in a facility with a number of machines in parallel. Each order asks for certain amounts of various different product types which can be produced concurrently. Each product type can be produced on a subset of the machines. Two extreme cases of machine environments are of interest. In the first case, each product type can be produced on one and only one machine which is dedicated to that product type. In the second case, all machines are identical and flexible; each product type can be produced by any one of the machines. Moreover, when a machine in this case switches over from one product type to another, no setup is required. Each order has a release date and a weight. Preemptions are not allowed. The objective is minimizing the total weighted completion time of the orders. Even when all orders are available at time 0, both types of machine environments have been shown to be NP-hard for any fixed number (≥2) of machines. This paper focuses on the design and analysis of approximation algorithms for these two machine environments. We also present empirical comparisons of the various algorithms. The conclusions from the empirical analyses provide insights into the trade-offs with regard to solution quality, speed, and memory space. © 2007 Springer Science+Business Media, LLC.
Identifier
38749134542 (Scopus)
Publication Title
Annals of Operations Research
External Full Text Location
https://doi.org/10.1007/s10479-007-0270-5
e-ISSN
15729338
ISSN
02545330
First Page
107
Last Page
123
Issue
1
Volume
159
Grant
DMI-0300156
Fund Ref
National Science Foundation
Recommended Citation
Leung, Joseph Y.T.; Li, Haibing; and Pinedo, Michael, "Scheduling orders on either dedicated or flexible machines in parallel to minimize total weighted completion time" (2008). Faculty Publications. 12868.
https://digitalcommons.njit.edu/fac_pubs/12868
