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Acton, F. S., Numerical Methods that Usually Work, Chapter 17, The Mathematical Association of America, Washington, D. C., 1990 (updated from the 1970 edition). [ Introductory numerical methods book, fun and lively in style.]

Arts, E. H. L., and Korst, J.H.M., Simulated Annealing and Boltzmann Machines, Wiley (Interscience), New York, 1989.

Baker, J. E., Adaptive Selection Methods for Genetic Algorithms, pp. 101-111, Proceedings of an International Conference on Genetic Algorithms and their Applications (J. J. Grefenstette, editor), Lawrence Erlbaum Associates, Hillsdale, NJ.

Boggs, P.T., Byrd, R.H. and Schnabel, R.B., Eds., Numerical Optimization 1984, SIAM, Philadelphia, 1985. [ A collection of papers presented at the SIAM optimization conference, varied and interesting approaches.]

Booker, L. B., Improving Search in Genetic Algorithms, pp. 61-73, Genetic Algorithms and Simulated Annealing (L. Davis, editor), Pitman, London, 1987.

Bounds, D. G., New Optimization Methods from Physics and Biology, Nature 329, 215-218, 1987.

Cauchy, A., Methode Generale pour la Resolution des Systemes d'Equations Simultanees, Comp. Rend. Acad. Sci. Paris, 536-538, 1847. [ Advanced article, Cauchy's steepest descent method.]

Cavicchio, D. J., Adaptive Search Using Simulated Evolution, Ph.D. Thesis, University of Michigan, Ann Arbor, MI, 1970.

Ciarlet, P.G., Introduction to Numerical Linear Algebra and Optimization, Cambridge University Press, Cambridge, Great Britain, 1989. [ Advanced optimization book, theoretical angle.]

Concus, P., Golub, G. H and O'Leary, D.P., A Generalized Conjugate Gradient Method for the Numerical Solution of Elliptic Partial Differential Equations, Sparse Matrix Computations, J. R. Bunch and D. J. Rose, Eds., Academic Press, New York, 1976, 309-332. [ Advanced article describing preconditioned conjugate gradient applications.]

Dahlquist, G. and Bjork, A., Numerical Methods, Prentice-Hall, Englewood Cliffs, New Jersey, 1974. [ Classic numerical methods book, covers numerous areas in broad detail.]

Darwin, C., On The Origin of Species, 1st edition (facsimile - 1964), Harvard University Press, Cambridge, MA, 1859.

Davis, L., Handbook of Genetic Algorithms, Van Nostrand Reinhold, New York, NY, 1991.

Dawkins, R., The Blind Watchmaker, Penguin, London, 1986.

De Jong, K. A., An Analysis of the Behavior of a Class of Genetic Adaptive Systems, Ph.D. Thesis, University of Michigan, Ann Arbor, MI., 1975.

Dennis, J.E. Jr. and Schnabel, R.B., Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Prentice-Hall, Englewood Cliffs, New Jersey, 1983. [ Advanced optimization book, providing theoretical background for algorithms.]

Dennis Jr., J.E. and More, J.J., Quasi-Newton Methods, Motivation and Theory, SIAM Review 19, 46-89, 1977. [ Advanced review of Quasi-Newton methods.]

Dembo, R.S. and Steihaug, T., Truncated-Newton Algorithms for Large-Scale Unconstrained Optimization, Math. Prog. 26, 190-212 (1983). [ Advanced article presenting the truncated Newton method in theoretical detail.]

Dixon, L.C.W., On the Impact of Automatic Differentiation on the Relative Performance of Parallel Truncated Newton and Variable Metric Algorithms, SIAM J. Opt. 1, 475-486, 1991. [ Review on automatic differentiation and its usage.]

Duff, I.S., Erisman, A. M. and Reid, J.K., Direct Methods for Sparse Matrices, Clarendon Press, Oxford (1986). [ Advanced textbook on direct methods for solving sparse linear systems.]

Evans, J.D., The Use of Pre-conditioning in Iterative Methods for Solving Linear Equations With Symmetric Positive Definite Matrices, J. Inst. Math. Applic. 4, 295-314, 1967. [ Advanced article introducing preconditioning for conjugate gradient methods.]

Fletcher, R., Practical Methods of Optimization, Second Edition, (A Wiley- Interscience Publication), John Wiley and Sons, Tiptree, Essex, Great Britain, 1987. [ Advanced book on optimization techniques.]

Fletcher, R. and Reeves, C.M., Function Minimization by Conjugate Gradients, Comp, J. 7, 149-154, 1964. [ Advanced article on using conjugate gradient for nonconvex functions.]

Floudas, C.A. and Pardalos, P. M., Eds., Recent Advances in Global Optimization, Princeton Series in Computer Science, Princeton University Press, New Jersey, 1991. [ Recent volume on various approaches to global optimization.]

George, A. and Liu, J.W., Computer Solution of Large Sparse Positive Definite Systems, Prentice-Hall, Englewood Cliffs, New Jersey, 1981. [ Advanced textbook on solving large sparse positive definite systems of equations.]

Gilbert, J.C. and Nocedal, J., Global Convergence Properties of Conjugate Gradient Methods for Optimization. SIAM J. Opt. 2, 21-42, 1992. [ Advanced article summa-
rizing the various conjugate gradient methods and their properties.

Gilbert, J.C., and Lemarechal, C., Some Numerical Experiments with Variable-Storage Quasi-Newton Algorithms, Math. Prog. 45, 407-435, 1989. [ Advanced article describing practical experience with limited-memory Quasi-Newton methods on large-scale crystallography and meteorology problems.]

Gill, P.E., Murray, W. and Wright, M. H., Numerical Linear Algebra and Optimization, Volume 1, Addison-Wesley, Redwood City, California, 1991. [ Introductory numerical linear algebra and optimization book.]

Gill, P.E., Murray, W. and Wright, M.H., Practical Optimization, Academic Press, New York, 1983. [ Standard reference book on practical optimization methods.]

Gill, P.E., Murray, W., Saunders, M. A. and Wright, M.H., Computing Forward-Difference Intervals for Numerical Optimization, SIAM J. Sci. Stat. Comput. 4, 310-321, 1983. [ Advanced article, excellent description on choosing finite-difference intervals.]

Goldberg, D. E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley, Reading, MA, 1989.

Golub, G.H. and Van Loan, C.F., Matrix Computations, Johns Hopkins University Press, Baltimore, Maryland, 1983. [ Excellent linear algebra book.]

Grefenstette, J. J., Optimization of Control Parameters for Genetic Algorithms, IEEE Trans. Syst., Man, Cyber. SMC-16, 122-128, 1986.

Grefenstette, J. J., Incorporating Problem Specific Knowledge into Genetic Algorithms, pp. 42-60, Genetic Algorithms and Simulated Annealing (L. Davis, editor), Pitman, London, 1987.

Griewank, A., On Automatic Differentiation, Mathematical Programming 1988, Kluwer Academic Publishers, Japan, 1988, pp. 83-107. [ Review on automatic differentiation.]

Hestenes, M.R., Conjugate Direction Methods in Optimization, Springer-Verlag, New York, 1980. [ Advanced textbook on methods related to conjugate gradient.]

Holland, J. H., Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI, 1975.

Hollstien, R. B., Artificial Genetic Adaptation in Computer Control Systems, Ph.D. Thesis, University of Michigan, Ann Arbor, MI., 1971.

Kirkpatrick, S., Gerlatt, C. D. Jr., and Vecchi, M. P., Optimization by Simulated Annealing, IBM Research Report RC 9355, 1982.

Kirkpatrick, S., Gerlatt, C. D. Jr., and Vecchi, M.P., Optimization by Simulated Annealing, Science 220, 671-680, 1983.

Kirkpatrick, S., Optimization by Simulated Annealing - Quantitative Studies, J. Stat. Phys. 34, 975-986, 1984.

Laarhoven, P. J. M. van, and Aarts, E. H. L., Simulated Annealing: Theory and Applications, Reidel, Dordrecht, Holland, 1987.

Lin, S., Computer Solutions of the Traveling Salesman Problem, Bell Syst. Tech. J. 44, 2245-2269, 1965.

Liu, D.C. and Nocedal, J., On the Limited Memory BFGS Method for Large Scale Optimization, Math. Prog. 45, 503-528, 1989. [ Advanced article presenting the limited-memory Quasi Newton method.]

Luenberger, D.G., Linear and Nonlinear Programming, Second Edition, Addison-Wesley, Reading, Massachusetts, 1984. [ Introductory optimization book, providing easy-to-grasp explanations of algorithmic strategies.]

Metropolis, N., Rosenbluth, A.W., Rosenbluth, M. N., Teller, A.H. and Teller, E., Equations of State Calculations by Fast Computing Machines, J. Chem. Phys. 21, 1087- 1092, 1958.

Nash, S.G., Solving Nonlinear Programming Problems using Truncated-Newton Techniques, Numerical Optimization 1984, P. T. Boggs, R. H. Byrd, and R. B. Schnabel, Eds., SIAM, Philadelphia, 1985, pp. 119-136. [ Advanced article presenting a practical truncated Newton algorithm.]

Nemhauser, G.L., Rinnooy Kan, A.H.G. and Todd, M.J., Eds., Handbook in Operations Research Management Science, Vol. 1, Optimization, Elsevier Science Publishers (North-Holland), Amsterdam, The Netherlands, and New York, 1989. [ Excellent volume on recent technique in optimization research.]

Parks, G. T., An Intelligent Stochastic Optimization Routine for Nuclear Fuel Cycle Design, Nucl. Technol. 89, 233-246, 1990.

Pincus, M., A Monte Carlo Method for the Approximate Solution of Certain Types of Constrained Optimization Problems, Oper. Res. 18, 1225-1228, 1970.

Powell, M.J.D., An Efficient Method for Finding the Minimum of a Function of Several Variables Without Calculating Derivatives, Comp. J. 7, 155-162, 1964. [ Advanced articles, presents Powell minimization method.]

Powell, M.J.D., Nonconvex Minimization Calculations and the Conjugate Gradient Method, Lecture Notes in Mathematics, Vol. 1066, pp. 122-141, 1984. [ Advanced review on conjugate gradient for nonconvex functions.]

Rall, L.B., Automatic Differentiation - Techniques and Applications, Lecture Notes in Computer Science 120, Springer-Verlag, Berlin, New York, 1981. [ Textbook on automatic differentiation.]

Randelman, R. E., and Grest, G.S., N-City Traveling Salesman Problem - Optimization by Simulated Annealings, J. Stat. Phys. 45, 885-890, 1986.

Schlick, T. and Overton, M., A Powerful Truncated Newton Method for Potential Energy Minimization, J. Comp. Chem. 8, 1025-1039, 1987. [ Article presenting development and application of a truncated Newton method to computational chemistry problems.]

Schlick, T. and Fogelson, A., TNPACK --- A Truncated Newton Minimization Package for Large-Scale Problems: I. Algorithm and Usage and II. Implementation Examples. ACM Trans. Math. Softw. 18, 41-111, 1992. [ Article describing a truncated-Newton minimization package TNPACK and illustrating its application in several scientific applications.]

Derreumaux, P., Zhang, G., Schlick, T., and Brooks, B., A Truncated Newton Minimizer Adapted for CHARMM and Biomolecular Applications, J. Comp. Chem. 15, 532-552, 1994. [ Article describing the adaptation of a minimization package for optimization of molecular structures.]

Schlick, T., Modified Cholesky Factorizations for Sparse Preconditioners, SIAM J. Sci. Stat. Comp. 14, 424-445, 1993. [ Article presenting practical strategies of choosing sparse preconditioners for optimization.]

Schlick, T., Optimization Methods in Computational Chemistry, Reviews in Computational Chemistry, Vol. III, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publisher, New York, pp 1-71, 1992. [ Review on optimization techniques in computational chemistry applications.]

Schnabel, R.B. and Eskow, E., A New Modified Cholesky Factorization, SIAM J. Sci. Stat. Comput. 11, 1136-1158, 1990. [ Advanced article presenting a new modified Cholesky factorization.]

Shanno, D.F., Conjugate Gradient Methods with Inexact Searches, Math. Oper. Res. 3, 244-256, 1978. [ Advanced article on conjugate gradient for nonconvex functions.]

Vanderbilt, D., and Louie, S. G., A Monte Carlo Simulated Annealing Approach to Optimization over Continuous Variables, J. Comput. Phys. 56, 259- 271, 1984.

Baeck, T., Evolutionary Algorithms in Theory and Practice, Oxford University Press, Oxford, 1995.

Hartmann D., Optimierung Balkenartiger Zylindeerschalen aus Stahlbeton mit Elastischem und Plastischem Werkstoffverhalten, Ph.D. Thesis, University of Dortmund, 1974.

Rechenberg I., Evolutionsstrategie: Optimierung Technischer Systeme nach Prinzipien der Biologischen Evolution, Frommann-Holzboog, Stuttgart, 1973.

Schwefel, H-P., Evolutionsstrategie und Numerische Optimierung, Dissertation, Technical University of Berlin, 1975.

Schwefel, H-P., Binäre Optimierung durch Somatische Mutation, Technical Report, Technical University of Berlin and Medical University of Hannover, 1975.

Schwefel, H-P., ``Collective Phenomena in Evolutionary Systems'', Preprints of the 31st Annual Meeting of the International Society for General System Research, Budapest 2, 1025-1033, 1987.

Schwefel, H-P., Evolution and Optimum Searching, Wiley Interscience, John Wiley & Sons, New York, 1995.