|A First Course in Linear Optimization||an intro to LP with software|
|Global Optimization Algorithms – Theory and Application –||book on heuristic methods|
|A Field Guide to Genetic Programming||book on general genetic programming|
|LP-book||an introduction to linear programming and the simplex method, with online exercises|
|Deterministic Modeling||Linear Optimization with Applications|
|Linear Optimization: Theory, methods, and extensions||Introduction to linear programming, sensitivity analysis, simplex and interior point methods|
|NEOS-Optimization-Guide||A comprehensive guide with intro, algorithms, resources|
|Convex Optimization||book by Stephen Boyd and Lieven Vandenberghe. more material on class webpages.|
|Tutorial on Geometric Programming||by Stephen Boyd et al. (PDF)|
|Various lectures by Hans Bruun Nielsen||optimization, least squares etc|
|Topology Optimization||for structural problems, MEMS|
|A course in combinatorial optimization||lecture notes by A. Schrijver|
|Knapsack Problems||free download of book on topic|
|MIP Theory and Practice||survey article by Bixby et al|
|Latest Advances in MIP Solvers||talk by Bixby et al|
|Integer Programming Software Systems||survey comparing CPLEX, XPRESS-MP, LINDO|
|Six Talks on MINLP||by Sven Leyffer|
|MIP/PDECON problems||by Sven Leyffer|
|Survey on convex MINLP||handout and presentation|
|Survey on nonconvex MINLP||by Burer and Letchford|
|MINLP survey paper||by P. Belotti et al|
|OR-Notes||by J. E. Beasley, deterministic and stochastic topics|
|OR Class Notes||by M. Trick, integer programming, dynamic programming etc|
|Tutorials on Stochastic Programming||from the COSP website|
|Introduction to Stochastic Programming||from the COSP site|
|Robust control, LMI||Various courses by Didier Henrion|
Optimization is a very lively area, hence standard textbooks become outdated very fast. Therefore only a very restricted and certainly subjective list of books is presented here, mainly extracted from the FAQs initiated by Gregory and presently maintained by R. Fourer.
Books on or containing a considerable amount of LP theory or practice:
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.
Juenger, M. et al.: Mixed Integer Programming Computation, Springer, 2009
50 Years of Integer Programming 1958-2008
Luenberger, D. G. and Ye, Yinyu: Introduction to Linear and Nonlinear Programming, Springer, 2008
Updated version of an old classic. Well suited for beginners
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
Now a table of books mainly devoted to nonlinear programming
Conn, A.R., Scheinberg, K., and Vicente, L.N.: Introduction to Derivative-Free Optimizati. SIAM:2009
First contemporary comprehensive treatment of optimization without derivatives
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.
Bjoerck, Ake : Numerical methods for least squares problems. Philadelphia, SIAM 1996
Very well written book with lots of nonstandard information.
Dempe, Stephan: Foundations of Bilevel Programming, Springer Verlag, 2002
Bilevel programming, Theory and algorithms.
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
M. Locatelli and F. Schoen: Global Optimization
Theory, Algorithms, and Applications
More, J.J. and Wright, St.: Optimization Software Guide. SIAM, 1993.
Contains overview and comments existing software, mainly commercial.
Nemhauser, G.L.: 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.
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