Publication Type
Journal Article
Version
submittedVersion
Publication Date
2006
Abstract
This paper proposes a new hybrid technique called partial parameter uniformization (hereafter PPU). The technique simplifies problems by ignoring the different values that certain problem parameters can take, which may facilitate the solution of some hard combinatorial optimization problems. PPU is applied to complex batch sizing and scheduling problems. Some information can be obtained from a discrete-time model in which job durations have been made uniform. This information is then exploited by a more detailed continuous-time model to generate feasible solutions and further improve these solutions. Good, or optimal solutions to the Westenberger and Kallrath Benchmark problems have been obtained in this way, at relatively low computational cost, as have solutions to the newer problems of Blömer and Günther.
Discipline
Business Administration, Management, and Operations
Research Areas
Operations Management
Publication
Computers and Operations Research
Volume
33
Issue
4
First Page
971
Last Page
993
ISSN
0305-0548
Identifier
10.1016/j.cor.2004.11.013
Publisher
Elsevier
Citation
Wang, Siqun and Guignard, Monique.
Hybridizing Discrete- and Continuous-Time Models for Batch Sizing and Scheduling Problems. (2006). Computers and Operations Research. 33, (4), 971-993.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/1914
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.cor.2004.11.013