Finite Capacity Scheduling - Large System Design

Rodney L. Martin

doi:10.4028/www.scientific.net/AMR.421.607

Paper Titles

Research and Design of MES Based on Real-Time Database in Iron & Steel Enterprise
p.586

Neural Network Based Expert System for Steel Bar Pipeline Fault Diagnosis
p.590

The Evaluation of Multi-Supplier Quality Competitiveness Based on TFN-AHP Method
p.595

An Effective Method for Manufacturing Data Integration Based on Resource Model
p.601

Finite Capacity Scheduling - Large System Design
p.607

An Optimization Opportunistic Maintenance Policy of Multi-Unit Series Production System
p.617

Research of Complex Plate-Type Cam Processing Based on MasterCAM
p.625

Studies of Rapid Tooling Spraying Technology Using Low Melting Metal Alloy
p.630

Concurrent Tolerance Design System Based on Manufacturing Context
p.634

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 421Finite Capacity Scheduling - Large System Design

Finite Capacity Scheduling - Large System Design

Abstract:

This paper presents the design principles for a large finite capacity scheduling system which takes into account alternative tools and machines. The system will produce tightly packed and stable schedules which in many cases will be close to optimal. The system can then be used as a platform for research into the application of decision making techniques, mathematical optimization, and other modern techniques.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 421)

Pages:

607-616

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.421.607

Citation:

Cite this paper

Online since:

December 2011

Authors:

Rodney L. Martin

Keywords:

Finite Capacity Scheduling, Manufacturing Scheduling, System Design

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Deming Lei, Fuzzy job shop scheduling problem with availability constraints, Computers & Industrial Engineering 58 (2010) 610–617

DOI: 10.1016/j.cie.2010.01.002

Google Scholar

[2] Umit Bilge, Murat Firat, Erinc Albey, A parametric fuzzy logic approach to dynamic part routing under full routing flexibility, Computers & Industrial Engineering 55 (2008) 15–33

DOI: 10.1016/j.cie.2007.11.013

Google Scholar

[3] Ersin Körpeoglu, Hande Yaman, M. Selim Aktürk, A multi-stage stochastic programming approach in master production scheduling, European Journal of Operational Research 213 (2011) 166–179

DOI: 10.1016/j.ejor.2011.02.032

Google Scholar

[4] Glen Wirth, Vincent de Gast, Marcus Tennant, Realizing the Benefits of Finite Capacity Scheduling to Manage Batch Production Systems WBF North American Conference, Baltimore, MD, USA, 30 April - 4 May 2007 http://www.systemsnavigator.com/sn_website/Documents/WBF2007NA-Wirth-deGast-Tennant.pdf

Google Scholar

[5] Susan A. Slotnick, Order acceptance and scheduling: A taxonomy and review, European Journal of Operational Research 212 (2011) 1–11

DOI: 10.1016/j.ejor.2010.09.042

Google Scholar

[6] H.Z. Jia, J.Y.H. Fuh, A.Y.C. Nee, Y.F. Zhang, Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems, Computers & Industrial Engineering 53 (2007) 313–320

DOI: 10.1016/j.cie.2007.06.024

Google Scholar

[7] Martin, R. L.; White C, "Finite capacity scheduling—packed placement sequence schedule", International Journal of Production Research, Vol. 43, No. 2, 15 January 2005, 405–446

DOI: 10.1080/0020754042000264545

Google Scholar

[8] Martin, R. L., "Finite capacity scheduling with mixed duration tooling trees", International Journal of Production Research, Vol 46, Issue 6, (2008)

DOI: 10.1080/00207540600919365

Google Scholar