Simulation-based optimization with surrogate models—Application to supply chain management

Computers and Chemical Engineering - Tập 29 - Trang 1317-1328 - 2005
Xiaotao Wan1, Joseph F. Pekny1, Gintaras V. Reklaitis1
1School of Chemical Engineering, Purdue University, West Lafayette, IN 47906, USA

Tài liệu tham khảo

Barton, R. R. (1994). Metamodeling: a state of the art review. In J. D. Tew, S. Manivannan, D. A. Sadowski, & A. F. Seila (Eds.), Proceedings of the 1994 Winter Simulation Conference (p. 237). Chambers, 2002, Process optimization via neural network metamodeling, International Journal of Production Economics, 79, 93, 10.1016/S0925-5273(00)00188-2 Fu, 2002, Optimization for simulation: Theory vs. practice, INFORMS Journal on Computing, 14, 192, 10.1287/ijoc.14.3.192.113 Greenwood, 1998, An investigation of the behavior of simulation response surface, European Journal of Operational Research, 110, 282, 10.1016/S0377-2217(97)00255-5 Jones, 1998, Efficient global optimization of expensive black-box functions, Journal of Global Optimization, 13, 455, 10.1023/A:1008306431147 Jung, J. Y., Blau, G., Pekny, J. F., Reklaitis, G. V., & Eversdyk, D. (in press). A simulation based optimization approaches to supply chain management under demand uncertainty. Computers and Chemical Engineering. Kleinman, 1999, Simulation-based optimization with stochastic approximation using common random numbers, Management Science, 45, 1570, 10.1287/mnsc.45.11.1570 Mackay, 1992, Bayesian interpolation, Neural Computation, 4, 415, 10.1162/neco.1992.4.3.415 Mackay, 1995, Probable networks and plausible predictions—A review of practical Bayesian methods for supervised neural networks, Computation in Neural Systems, 6, 496, 10.1088/0954-898X/6/3/011 Nedderrneijer, H. G., van Oortmarssen, G. J., Piersma, N., & Dekker, R. (2000). A framework for response surface methodology for simulation optimization. In Proceedings of the 1999 Winter Simulation Conference. Owen, 1998, Latin supercube sampling for very-high dimensional simulations, ACM Transactions on Modeling and Computer Simulation, 8, 71, 10.1145/272991.273010 Sabuncuoglu, 2002, Simulation metamodelling with neural networks: An experimental investigation, International Journal of Production Research, 40, 2483, 10.1080/00207540210135596 Sacks, 1989, Design and analysis of computer experiments (with discussion), Statistical Science, 4, 409, 10.1214/ss/1177012413 Sasena, 2002, Exploration of metamodeling sampling criteria for constrained global optimization, Engineer Optimization, 34, 263, 10.1080/03052150211751 Schölkof, 2002 Spall, 1992, Multivariate stochastic approximation using a simultaneous perturbation gradient approximation, IEEE Transactions on Automatic Control, 37, 332, 10.1109/9.119632 Spall, 1998, Implementation of the simultaneous perturbation algorithm for stochastic optimization, IEEE Transactions on Aerospace and Electronic Systems, 34, 817, 10.1109/7.705889 Spall, J. C. (1999). Stochastic optimization and the simultaneous perturbation method. In Proceedings of the 1999 Winter Simulation Conference. Subramanian, 2000, A simulation-optimization framework for addressing combinatorial and stochastic aspects of R&D pipeline management problem, Computers and Chemical Engineering, 24, 1005, 10.1016/S0098-1354(00)00535-4 Subramanian, 2003, Computational framework for supply chain analysis, AIDIC Conference Series Van Gestel, 2002, Financial time series prediction using least squares support vector machines within the evidence framework, IEEE Transactions on Neural Networks, 12, 808 Vapnik, 1998 Vapnik, 1999, An overview of statistical learning theory, IEEE Transactions on Neural Networks, 10, 988, 10.1109/72.788640