References and Additional Resources – Engineering Optimization

References and Additional Resources

Books on Optimization

  1. Beveridge, G. S. G. and R. S.Schechter, Optimization: Theory and Practice, McGraw‐Hill, New York, 1970.
  2. Chong, E. P. K. and S. H.Zak, An Introduction to Optimization, 2nd Edition, John Wiley & Sons, Inc., New York, 2001.
  3. Edgar, T. F., D. M.Himmelblau, and L. S.Lasdon, Optimization of Chemical Processes, McGraw‐Hill, New York, 2001.
  4. Hillier, F. S. and G. J.Lieberman, Introduction to Operations Research, McGraw‐Hill, New York, 2001.
  5. Nocedal, J. and S. J.Wright, Numerical Optimization, Springer‐Verlag, New York, 1999.
  6. Rao, S. S., Engineering Optimization: Theory and Practice, 4th Edition, John Wiley & Sons, Inc., Hoboken, 2009.
  7. Ravindran, A., K. M.Ragsdell, and G. V.Reklaitis, Engineering Optimization—Methods and Applications, John Wiley & Sons, Inc., Hoboken, 2006.
  8. Snyman, J. A., Practical Mathematical Optimization, Springer, New York, 2005.

Books on Probability and Statistics

  1. Bethea, R. M. and R. R.Rhinehart, Applied Engineering Statistics, Taylor & Francis, Boca Raton, FL, 1991. ISBN 0‐8247‐8503‐7.
  2. Rhinehart, R. R., Instrument and Automation Engineers’ Handbook, Vol I, Process Measurement and Analysis, 5th Edition, B.Liptak and K.Venczel, Editors, Section 1.10, “Uncertainty—Estimation, Propagation, & Reporting,” Taylor & Francis, CRC Press, Boca Raton, FL, 2016a.
  3. Rhinehart, R. R., Nonlinear Regression Modeling for Engineering Applications: Modeling, Model Validation, and Enabling Design of Experiments, John Wiley & Sons, Inc., Hoboken, 2016b. ISBN 9781118597965.

Books on Simulation

  1. Law, A. M. and W. D.Kelton, Simulation Modeling and Analysis, 2nd Edition, McGraw Hill, New York, 1991.

Specific Techniques

  1. Akaho’s Approximation for Normal Least Squares—S.Akaho, “Curve Fitting That Minimizes the Mean Square of Perpendicular Distances from Sample Points,” Proc. SPIE 2060, Vision Geometry II, 237, December 1, 1993. doi:10.1117/12.164998; 10.1117/12.164998.
  2. Best‐of‐N Method—Iyer, M. S. and R. R.Rhinehart, “A Method to Determine the Required Number of Neural Network Training Repetitions,” IEEE Transactions on Neural Networks, Vol. 10, No. 2, 1999, pp. 427–432.
  3. Dynamic Programming—Rhinehart, R. R. and J. D.Beasley, “Dynamic Programming for Chemical Engineering Applications,” Chemical Engineering, Vol. 94, No. 18, 1987, pp. 113–119. That article was the basis for the chapter, Rhinehart, R. R. and J. D.Beasley, Encyclopedia of Chemical Processing and Design, Vol. 44, J.J.McKetta, Editor, “Dynamic Programming,” 1993, pp. 411–424.
  4. Generating Gaussian Noise—Box, G. E. P. and M. E.Muller, “A Note on the Generation of Random Normal Deviates,” The Annals of Mathematical Statistics, Vol. 29, No. 2, 1958, pp. 610–611.
  5. Initialization of Players—Manimegalai‐Sridhar, U., A.Govindarajan, and R. R.Rhinehart, “Improved Initialization of Players in Leapfrogging Optimization,” Computers & Chemical Engineering, Vol. 60, 2014, pp. 426–429.
  6. Leapfrogging—Rhinehart, R. R., M.Su, and U.Manimegalai‐Sridhar, “Leapfrogging and Synoptic Leapfrogging: A New Optimization Approach,” Computers & Chemical Engineering, Vol. 40, 2012, pp. 67–81.
  7. Snyman, J. A. and L. P.Fatti, “A Multi‐Start Global Minimization Algorithm with Dynamic Search Trajectories,” Journal of Optimization Theory and Applications, Vol. 54, 1987, pp. 121–141.
  8. Steady State Identification—Bhat, S. A. and D. N.Saraf, “Steady‐State Identification, Gross Error Detection, and Data Reconciliation for Industrial Process Units,” Industrial and Engineering Chemistry Research, Vol. 43, No. 15, 2004, pp. 4323–4336.
  9. Steady State Identification—Cao, S. and R. R.Rhinehart, “An Efficient Method for On‐Line Identification of Steady‐State,” Journal of Process Control, Vol. 5, No. 6, 1995, pp. 363–374.
  10. Steady State Identification—Shrowti, N., K.Vilankar, and R. R.Rhinehart, “Type‐II Critical Values for a Steady‐State Identifier,” Journal of Process Control, Vol. 20, No. 7, pp. 885–890, 2010.
  11. Steady State Identification—vonNeumann, J., R.Kent, H.Bellison, and B.Hart, “The Mean Square Successive Difference,” The Annals of Mathematical Statistics, Vol. 12, 1941, pp. 153–162.
  12. Stochastic Convergence—Rhinehart, R. R., “Convergence Criterion in Optimization of Stochastic Processes,” Computers & Chemical Engineering, Vol. 68, 2014, pp. 1–6.

Selected Landmark Papers

  1. Data Reconciliation—Mah, R. S., G. M.Stanley, and D. M.Downing, “Reconciliation and Rectification of Process Flow and Inventory Data,” Industrial & Engineering Chemistry, Process Design and Development, Vol. 15, No. 1, 1976, pp. 175–183.
  2. Differential Evolution—Storn, R. and K.Price, “Differential Evolution—A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces,” Journal of Global Optimization, Vol. 11, 1997, pp. 341–359. doi:10.1023/A:1008202821328.
  3. GRG—Lasdon, L. S., R. L.Fox, and M. W.Ratner, “Nonlinear Optimization Using the Generalized Reduced Gradient Method,” AD‐774 723, Prepared for the Office of Naval Research, National Technical information Service, US Department of Commerce, Springfield, VA, 1973, Technical Memorandum No. 325.
  4. Hooke–Jeeves—Hooke, R. and T. A.Jeeves, “‘Direct Search’ Solution of Numerical and Statistical Problems,” Journal of the Association for Computing Machinery (ACM), Vol. 8, No. 2, 1961, pp. 212–229. doi:10.1145/321062.321069.
  5. Levenberg–Marquardt—Levenberg, K., “A Method for the Solution of Certain Non‐Linear Problems in Least Squares,” Quarterly of Applied Mathematics, Vol. 2, 1944, pp. 164–168. Marquardt, D., “An Algorithm for Least‐Squares Estimation of Nonlinear Parameters,” SIAM Journal on Applied Mathematics, Vol. 11, No. 2, 1963, 431–441. doi:10.1137/0111030.
  6. Particle Swarm—Kennedy, J. and R.Eberhart, “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks, Vol. 4, 1995, pp. 1942–1948. doi:10.1109/ICNN.1995.488968.
  7. Simplex—Nelder–Mead—Nelder, J. A. and R.Mead, “A Simplex Method for Function Minimization,” Computer Journal, Vol. 7, 1965, pp. 308–313. doi:10.1093/comjnl/7.4.308.
  8. Simplex—Spendley–Hext–Himsworth—Spendley, W., G. R.Hext, and F. R.Himsworth, “Sequential Application of Simplex Designs in Optimization and Evolutionary Operation,” Technometrics, Vol. 4, 1962, pp. 441–461.

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