Page 160 - Data Science Algorithms in a Week
P. 160
144 Alfonso T. Sarmiento and Edgar Gutierrez
Laskari, E., Parsopoulos, K., & Vrahatis, M. (2002). Particle swarm optimization for
minimax problems. In Proceedings of the 2002 IEEE Congress on Evolutionary
Computation, Honolulu, HI.
Lee, H., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains.
MIT Sloan Management Review, 38(3), 93–102.
Lee, J., Lee, S., Chang, S. & Ahn, B. (2005). A Comparison of GA and PSO for excess
return evaluation in stock markets. International Work Conference on the Interplay
between Natural and Artificial Computation - IWINAC 2005.
Lertpattarapong, C. (2002). Applying system dynamics approach to the supply chain
management problem. Master Thesis, Sloan School of Management, Massachusetts
Institute of Technology, Cambridge, MA.
Macedo, J. (1989). A reference approach for policy optimization in system dynamic
models. System Dynamics Review, 5(2), 148–175.
Michalewicz, Z. & Fogel, D. (2000). How to solve it: modern heuristics. Berlin,
Germany: Springer.
Mohapatra, P. & Sharma, S. (1985). Synthetic design of policy decisions in system
dynamic models: a modal control theoretical approach. System Dynamics Review,
1(1), 63–80.
Nagatani, T. & Helbing, D. (2004). Stability analysis and stabilization strategies for
linear supply chains. Physica A, 335(3/4), 644–660.
O’Donnell, T., Maguire, L., McIvor, R. & Humphreys, P. (2006). Minimizing the
bullwhip effect in a supply chain using genetic algorithms. International Journal of
Production Research, 44(8), 1523–1543.
Ortega, M. & Lin, L. (2004). Control theory applications to the production-inventory
problem: a review. International Journal of Production Research, 42(11), 2303–
2322.
Özcan, E. & Yilmaz, M. (2007). Particle Swarms for Multimodal Optimization. (2007).
In Proceedings of the 2007 International Conference on Adaptive and Natural
Computing Algorithms, Warsaw, Poland.
Perea, E., Grossmann, I., Ydstie, E., & Tahmassebi, T. (2000). Dynamic modeling and
classical control theory for supply chain management. Computers and Chemical
Engineering, 24(2/7), 1143–1149.
Poirier, C. & Quinn, F. (2006). Survey of supply chain progress: still waiting for the
breakthrough. Supply Chain Management Review, 10(8), 18–26.
Press, W., Teukolsky, S., Vetterling, W. & Flannery, B. (1992). Numerical recipes in C:
the art of scientific computing. Cambridge, England: Cambridge University Press.
Powell, M. (1964). An efficient method for finding the minimum of a function of several
variables without calculating derivatives. The Computer Journal, 7(2), 155-162.
Riddalls, C. and Bennett, S. (2002). The stability of supply chains. International Journal
of Production Research, 40(2), 459–475.