Research on an Improved Genetic Algorithm for Logistics Distribution Path Optimization-Reference-Cited by-同舟云学术

Research on an Improved Genetic Algorithm for Logistics Distribution Path Optimization

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Asia-Pacific Conference on Intelligent Medical 2018 & International Conference on Transportation and Traffic Engineering 2018 on - APCIM & ICTTE 2018
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Author:

Sun Xue¹,Wei Kai-Cheng²,Wu Chao-Chin²,Yang Chih-Kuang²,Chen Liang-Rui³

Affiliation:

1. College of Urban Rail Transit and Logistics, Beijing Union University, Beijing, China and Department of Electrical Engineering, National Changhua University of Education, Changhua, Taiwan

2. Department of Computer Science and Information Engineering, National Changhua University of Education, Changhua, Taiwan

3. Department of Electrical Engineering, National Changhua University of Education, Changhua, Taiwan

Publisher

ACM Press

Reference18 articles.

1. Dobrzańska, M., Dobrzański, P., and Śmieszek, M. 2013. Modern logistics in health service. Modern Management Review, 18(20 (3)), 53--64.

2. Sheu, J. B. 2007. An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E: Logistics and Transportation Review, 43(6), 687--709.

3. Kułyk, P., Michałowska, M., and Kotylak, S. 2017. Assessment of customer satisfaction with logistics service in the light of the results of the research. Management. 21(1), 205--222.

4. Huang, X., and Song, L. 2018. An emergency logistics distribution routing model for unexpected events. Annals of Operations Research. 269(1-2), 223--239.

5. Li Z., Chen X. H., and Wang H. 2012. Buckling optimization of composite laminate using modified ant colony optimization. J. Shanghai Jiaotong Univ. (Sci.). Vol.46, pp.768--773.

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