Ottimizzazione stocastica (Italian Wikipedia)

Analysis of information sources in references of the Wikipedia article "Ottimizzazione stocastica" in Italian language version.

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archive.org

Zhigljavsky, A. A., Theory of Global Random Search, Kluwer Academic, 1991.

doi.org

dx.doi.org

Fu, M. C., Optimization for Simulation: Theory vs. Practice, in INFORMS Journal on Computing, (con discussioni di S. Andradóttir, P. Glynn e J. P. Kelly), vol. 14, 2002, pp. 192–227, DOI:10.1287/ijoc.14.3.192.113.
Robbins, H., Monro, S., A Stochastic Approximation Method, in Annals of Mathematical Statistics, vol. 22, 1951, pp. 400–407, DOI:10.1214/aoms/1177729586.
J. Kiefer, J. Wolfowitz, Stochastic Estimation of the Maximum of a Regression Function, in Annals of Mathematical Statistics, vol. 23, 1952, pp. 462–466, DOI:10.1214/aoms/1177729392.
Spall, J. C., Multivariate Stochastic Approximation Using a Simultaneous Perturbation Gradient Approximation, in IEEE Transactions on Automatic Control, vol. 37, 1992, pp. 332–341, DOI:10.1109/9.119632.
S. Kirkpatrick, C. D. Gelatt; M. P. Vecchi, Optimization by Simulated Annealing, in Science, vol. 220, n. 4598, 1983, pp. 671–680, DOI:10.1126/science.220.4598.671, PMID 17813860.
Akbar Nayeem, Jorge Vila; Harold A. Scheraga, A comparative study of the simulated-annealing and monte carlo-with-minimization approaches to the minimum-energy structures of polypeptides: [met]-enkephalin, in J. Comp. Chem., vol. 12, n. 5, 1991, pp. 594–605, DOI:10.1002/jcc.540120509.
W. Wenzel, K. Hamacher, Stochastic tunneling approach for global optimization of complex potential energy landscapes, in Phys. Rev. Lett., vol. 82, 1999, p. 3003, DOI:10.1103/PhysRevLett.82.3003.
E. Marinari, G. Parisi, Simulated tempering: A new monte carlo scheme, in Europhys. Lett., vol. 19, 1992, p. 451, DOI:10.1209/0295-5075/19/6/002.

jhuapl.edu

Spall, J. C., Introduction to Stochastic Search and Optimization, Wiley, 2003.
Spall, J. C., Multivariate Stochastic Approximation Using a Simultaneous Perturbation Gradient Approximation, in IEEE Transactions on Automatic Control, vol. 37, 1992, pp. 332–341, DOI:10.1109/9.119632.

nih.gov

ncbi.nlm.nih.gov

S. Kirkpatrick, C. D. Gelatt; M. P. Vecchi, Optimization by Simulated Annealing, in Science, vol. 220, n. 4598, 1983, pp. 671–680, DOI:10.1126/science.220.4598.671, PMID 17813860.

oadoi.org

Fu, M. C., Optimization for Simulation: Theory vs. Practice, in INFORMS Journal on Computing, (con discussioni di S. Andradóttir, P. Glynn e J. P. Kelly), vol. 14, 2002, pp. 192–227, DOI:10.1287/ijoc.14.3.192.113.
Robbins, H., Monro, S., A Stochastic Approximation Method, in Annals of Mathematical Statistics, vol. 22, 1951, pp. 400–407, DOI:10.1214/aoms/1177729586.
J. Kiefer, J. Wolfowitz, Stochastic Estimation of the Maximum of a Regression Function, in Annals of Mathematical Statistics, vol. 23, 1952, pp. 462–466, DOI:10.1214/aoms/1177729392.
Akbar Nayeem, Jorge Vila; Harold A. Scheraga, A comparative study of the simulated-annealing and monte carlo-with-minimization approaches to the minimum-energy structures of polypeptides: [met]-enkephalin, in J. Comp. Chem., vol. 12, n. 5, 1991, pp. 594–605, DOI:10.1002/jcc.540120509.
W. Wenzel, K. Hamacher, Stochastic tunneling approach for global optimization of complex potential energy landscapes, in Phys. Rev. Lett., vol. 82, 1999, p. 3003, DOI:10.1103/PhysRevLett.82.3003.
E. Marinari, G. Parisi, Simulated tempering: A new monte carlo scheme, in Europhys. Lett., vol. 19, 1992, p. 451, DOI:10.1209/0295-5075/19/6/002.

psu.edu

citeseer.ist.psu.edu

S. Kirkpatrick, C. D. Gelatt; M. P. Vecchi, Optimization by Simulated Annealing, in Science, vol. 220, n. 4598, 1983, pp. 671–680, DOI:10.1126/science.220.4598.671, PMID 17813860.

web.archive.org

W. Wenzel, Stochastic Optimization Methods, su iwrwww1.fzk.de. URL consultato il 24 aprile 2009 (archiviato dall'url originale il 1º giugno 2009).
Goldberg, D. E., Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989 (archiviato dall'url originale il 19 luglio 2006).