Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry-Reference-Cited by-同舟云学术

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

Published:2014-01-06 Issue:1 Volume:10 Page:
ISSN:1735-5702
Container-title:Journal of Industrial Engineering International
language:en
Short-container-title:J Ind Eng Int

Author:

Izadi Arman,Kimiagari Ali mohammad

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering

Link

http://link.springer.com/content/pdf/10.1186/2251-712X-10-1.pdf

Reference33 articles.

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3. Arostegui MA Jr, Kadipasaoglub SN, Khumawala BM: An empirical comparison of tabu search, simulated annealing, and genetic algorithms for facilities location problem. Int J Prod Econ 2006, 103: 742–754. 10.1016/j.ijpe.2005.08.010

4. Chopra S: Designing the distribution network in a supply chain. Transp Res E 2003, 39: 123–140. 10.1016/S1366-5545(02)00044-3

5. Daskin MS: Network and Discrete Location: Models, Algorithms, and Applications. New York: John Wiley & Sons; 1995.

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