interior point optimization

a bibliography on interior point methods and integer programming,

optimization and matrix theory

a bibliography by H. Wolkowicz,

Euclidian Distance completion

a bibliography by H. Wolkowicz,

Quadratic Assignment Problem

a bibliography by H. Wolkowicz,

Semidefinite Programming

a bibliography by H. Wolkowicz,

A Field Guide to Genetic Programming

book on general genetic programming

LP with GLPK

an introduction to linear programming and the GNU LP kit,

LP-book

an introduction to linear programming and the simplex method, with online exercises

Applications of optimization with Xpress-MP

LP/MILP modelling, many applications

Deterministic Modeling

Linear Optimization with Applications

Linear Optimization: Theory, methods, and extensions

Introduction to linear programming, sensitivity analysis, simplex and interior point methods

A Primer in Column Generation

for LP, IP incl large scale practical problems

Selected Topics in Column Generation

in particular from dual perspective

NEOS-Guide-Optimization-Tree

A short introduction into the field of optimization in general with some basic theory and pointers to solvers

Nonlinear Programming Review

Introductory survey article on NLP methods including for large scale problems; PS and PDF formats.

Convex Optimization

book by Stephen Boyd and Lieven Vandenberghe. more material on class webpages.

Tutorial on Geometric Programming

by Stephen Boyd et al. (PDF)

Methods for Non-Linear Least Squares Problems

lecture notes by H. B. Nielsen et al

Unconstrained Optimization

lecture notes by H. B. Nielsen et al

Topology Optimization

for structural problems, MEMS

A course in combinatorial optimization

lecture notes by A. Schrijver

OR-courses

a list of courses covering diverse fields of optimization, operations research, and management science

Solving Real World Linear Programs

survey article by Bixby

MIP Theory and Practice

survey article by Bixby et al

Integer Programming Software Systems

survey comparing CPLEX, XPRESS-MP, LINDO

MINLP Tutorial

handout and presentation

OR-Notes

by J. E. Beasley, deterministic and stochastic topics

Practical Multiobjective Optimisation

introduction with survey of methods

OR Class Notes

Integer programming, Networks, dynamic programming, stochastic dynamic programming, OR-methods overview and management science.

Stochastic Programming: Computational Issues and Challenges

Survey article by Suvrajeet Sen

Introduction to Stochastic Programming

from the COSP site

Robust control, LMI

Various courses by Didier Henrion

Mathematical Programming Glossary.

For an explanation of terms used in optimization consult this dictionary.

Bertsimas, D. and Tsitsiklis, J.: Introduction to Linear Optimization. Athena Scientific, 1997. Graduate-level text on linear programming, network flows, and discrete optimization.

Maros, I., Computational Techniques of the Simplex Method Recent comprehensive monograph

Dantzig, G. B.: Linear Programming and Extensions, Princeton University Press, 1963. The most widely cited early textbook in the field.

Dantzig, George B. and Thapa, Mukund N.: Linear Programming 1: Introduction, Springer Verlag, 1997.

Luenberger, D. G.: Introduction to Linear and Nonlinear Programming, Addison Wesley, 1984. Updated version of an old classic. Well suited for beginners.

Nash, S. and Sofer, A.: Linear and Nonlinear Programming, McGraw-Hill, 1996.

Roos, C., Terlaky T. and Vial, J. Ph.: Theory and Algorithms for Linear Optimization: An Interior Point Approach. John Wiley, Chichester, 1997.

Schrijver, A.: Theory of Linear and Integer Programming, John Wiley, 1999. Advanced, very well written.

Vanderbei, R. J.: Linear Programming: Foundations and Extensions. Springer, 1996. Balanced coverage of simplex and interior-point methods. Source code available on-line for all algorithms presented.

Williams, H.P., Model Building in Mathematical Programming, John Wiley 1999, 4th edition. Little on algorithms, but excellent for learning what makes a good model.

Wright, St. J.: Primal-Dual Interior-Point Methods. SIAM Publications, 1997. Covers theoretical, practical and computational aspects of the most important and useful class of interior-point algorithms.

Ye, Yinyu: Interior Point Algorithms: Theory and Analysis. John Wiley, 1997.

Kellerer, H. et al: Knapsack Problems. Springer-Verlag, 2003.

Avriel, M. and Golany, B.: Mathematical Programming for Industrial Engineers. Marcel Dekker:1996. Contains introductory chapters to several areas of mathematical optimization. well suited for beginners.

Bonnans, J.F., Gilbert, J.C., Lemarechal, C., Sagastizabal, C.A.: Numerical Optimization (2nd edition). Springer: 2006. Both theory and details on implementations; nonsmooth optimization, interior-point methods etc.

Bertsekas, Dimitri P.: Nonlinear Programming, second edition. Athena Scientific, 1999.

Bjoerck, Ake : Numerical methods for least squares problems. Philadelphia, SIAM 1996. Very well written book with lots of nonstandard information.

Dennis, E. and Schnabel, B.: Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Prentice Hall, 1983. (reprinted by SIAM) (a classic in its field).

Dempe, Stephan; Kalashnikov, Vyacheslav (Eds.): Optimization with Multivalued Mappings. Springer Verlag, 2006. Bilevel programming, MPECs, multivalued set-valued optimization.

Du, D.-Z. and Pardalos, P.: Minimax and Applications. Springer, 1995.

Fiacco, A. and McCormick, G. P.: Sequential Unconstrained Minimization Techniques. reprinted by SIAM. (A classic from 1968, given new life by the interior point LP methods.)

Fletcher, R.: Practical Methods of Optimization. John Wiley, 2000. "The" reference at the date of its printing.

Gill, Ph.E., Murray, W. and Wright, M.: Practical methods of optimization. New York:Acad. Press 1982 (a bit dated with respect to methods, but with many hints for practitioners)

Hansen, E, and G.W. Walster: Global Optimization Using Interval Analysis. Dekker, 2003. (second edition)

Horst R., Pardalos P., and Thoai, V.: Introduction to global optimization. Springer, 1995.

Horst R. and Pardalos P.: Handbook of Global Optimization. Springer, 1994.

Kelley, C.T.: Iterative methods of optimization. Philadelphia: SIAM 1999 downloadable.

Kelley, C.T.: Iterative methods for Linear and Nonlinear Equations. Philadelphia: SIAM 1995 downloadable.

Luenberger, D.: Introduction to Linear and Nonlinear Programming. Addison Wesley, 1984. (Updated version of an old classic. Well suited for beginners.)

Miettinen,K.: Nonlinear Multiobjective Optimization, Springer. 1999.

More, J.J. and Wright, St.: Optimization Software Guide. SIAM, 1993. Contains overview and comments existing software, mainly commercial.

Nash, S. and Sofer, A.: Linear and Nonlinear Programming. McGraw-Hill, 1996.

Nemhauser, G.L., Rinnooy Kan,A.H.G. and Todd, M.J.: Optimization. (Handbook in Operations Research and Management Science Vol I). North Holland, 1989. Contains excellent introductions to severals areas of optimization.

Nocedal, J. and Wright, St.: Numerical Optimization, 2nd ed.. Springer Verlag, 2006. Very well written modern introduction into continuous optimization.

Pinter, J.D.: Global Optimization in Action. Springer, 1996. Book received 2000 INFORMS Computing Society Prize

Pinter, J.D.: Computational Global Optimization in Nonlinear Systems. Lionheart Publ., 2001. short e-book, demo software included

Pinter, J.D.: Global Optimization with Maple, Maplesoft, 2006. interactive e-book

Spellucci, P.: Numerische Verfahren der nichtlinearen Optimierung. Birkhäuser, Basel 1993 (in German).
course_script_1 / course_script_2

Tawarmalani, M. and Sahinidis, N. V.: Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming. Springer, 2002 . Based on BARON software.

Griewank, A.: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, SIAM 2000; first comprehensive treatment of AD

Corliss, G. et al (eds.): Automatic Differentiation of Algorithms: From Simulation to Optimization Springer 2002; Survey chapter, extensive applications chapters, and bibliography

Bücker, M. et al (eds.): Automatic Differentiation - Applications, Theory and Implementations Springer 2006; covers the state of the art in automatic differentiation theory and practice

Special Issue on the Next 10 Years of Constraint Programming, downloadable (2007), Intro and five articles

Roberto Battiti, Mauro Brunato and Franco Mascia: Reactive Search and Intelligent Optimization, downloadable (2007), integrates machine learning techniques

Dorigo, M., and Stützle, Th.: Ant Colony Optimization, MIT Press, 2004: comprehensive coverage of this metaheuristic including software

Corne D., Dorigo, M., and Glover, F.: New Ideas in Optimization: Chapters on various methods: Simulated Annealing, Genetic Programming, Tabu Search, Differential Evolution etc

Michalewicz, Z., Fogel, D.B.: How to Solve It: Modern Heuristics, Springer Verlag 2000

Siarry, P. and Michalewicz, Z.: Advances in Metaheuristics for Hard Optimization, Springer Verlag 2007