Dynamic Controls of Genetic Algorithm Scheduling in Supply Chain
Jia Yee Chai*, Tatsuhiko Sakaguchi**, and Keiichi Shirase*
*Graduate School of Engineering, Kobe University, 1-1 Rokkodai, Nada-Ku, Kobe 657-8501, Japan
**Toyohashi University of Technology, 1-1 Hibarigaoka, Tempaku-cho, Toyohashi-shi, Aichi-ken 441-8580, Japan
-  Y. Tanimizu, Y. Maeda, C. Ozawa, and N. Sugimura, “A study on dynamic supply chain considering production schedules – parallel scheduling for orders,” Proc. of 51st ISCIE, pp. 83-84, 2007 (in Japanese).
-  T. Kaihara, “Multi-agent based supply chain modeling with dynamic environment,” International Journal of Production Economics 85, pp. 263-269, 2003.
-  H. L. Young, S. J. Chan, and M. Chiung, “Advanced planning and scheduling with outsourcing in manufacturing supply chain,” Computers & Industrial Engineering 43, pp. 351-374, 2003.
-  S. H. Zegordi et at., “A novel genetic algorithm for solving production and transportation scheduling in a twostage supply chain,” Computers & Industrial Engineering, doi:10.1016/j.cie.2009.06.012, 2009.
-  J. Y. Chai, T. Sakaguchi, and K. Shirase, “Penalty Distribution Method for Scheduling Based Supply Chain Management,” The 41st CIRP Conference on Manufacturing System, pp. 261-265, 2009.
-  J. Y. Chai, T. Sakaguchi, K. Shirase, “Reactive scheduling based multi objectives negotiation for dynamic supply chain model,” Proceeding of Leading Edge Manufacturing in 21st Century, Kyushu, Japan, pp. 655-660, 2007.
-  T. Sakaguchi, Y. Tanimizu, T. Miyamae, Y. Maeda, K. Shirase, and N. Sugimura, “Improvement of crossover operator in genetic algorithm for reactive scheduling,” Proc. of the 3rd International Conference on Leading Edge Manufacturing in 21st century, pp. 427-432, 2005.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.