A Problem-Specific and Effective Metaheuristic for Flexibility Design
AbstractMatching uncertain demand with capacities is notoriously hard. Operations managers can use mix-flexible resources to shift excess demands to unused capacities. To find the optimal configuration of a mix-flexible production network, a flexibility design problem (FDP) is solved. Existing literature on FDPs provides qualitative structural insights, but work on solution methods is rare. We contribute the first metaheuristic which integrates these structural insights and is specifically tailored to solve FDPs. Our genetic algorithm is compared to commercial solvers on instances of up to 15 demand types, resources, and 500 demand scenarios. Experimental evidence shows that in the realistic case of flexible optimal configurations, it dominates the comparison methods regarding runtime and solution quality.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz in its series Working Papers with number 1001.
Length: 24 pages
Date of creation: 28 Jan 2010
Date of revision: 28 Jan 2010
Contact details of provider:
Postal: Haus Recht und Wirtschaft I, Jakob-Welder-Weg 9, D-55128 Mainz
Phone: +49 6131 39-22223
Web page: http://wiwi.uni-mainz.de/index.html
More information through EDIRC
Flexibility; Metaheuristic; Network Design;
Find related papers by JEL classification:
- M11 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - Production Management
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kauder, S. & Meyr, H., 2009. "Strategic network planning for an international automotive manufacturer," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 36058, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
- Seyed M. Iravani & Mark P. Van Oyen & Katharine T. Sims, 2005. "Structural Flexibility: A New Perspective on the Design of Manufacturing and Service Operations," Management Science, INFORMS, vol. 51(2), pages 151-166, February.
- Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
- Wallace J. Hopp & Eylem Tekin & Mark P. Van Oyen, 2004. "Benefits of Skill Chaining in Serial Production Lines with Cross-Trained Workers," Management Science, INFORMS, vol. 50(1), pages 83-98, January.
- William C. Jordan & Stephen C. Graves, 1995. "Principles on the Benefits of Manufacturing Process Flexibility," Management Science, INFORMS, vol. 41(4), pages 577-594, April.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lehrstuhl Wälde).
If references are entirely missing, you can add them using this form.