Optimization Bookstore

Suggestions of additional titles or commentary are welcome. Send to info@ampl.com.

The AMPL Book

• R. Fourer, D.M. Gay and B.W. Kernighan, AMPL: A Modeling Language for Mathematical Programming, second edition. Duxbury Press / Brooks/Cole Publishing Company, 2002. The basic guide and reference for the AMPL modeling language and system. Usually ships within 24 hours when in stock.

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  You can also order from the publisher.

General Optimization Topics

• H.T. Lau, A Numerical Library in C for Scientists and Engineers. CRC Press, 1995. Includes a section on optimization; comes with a disk.

• G.L. Nemhauser, A.H.G. Rinnooy Kan and M.J. Todd (editors), Optimization. Handbooks in Operations Research and Management Science, volume 1. North-Holland, 1989. A broad reference with large biliography. Entries are at a fairly advanced level.

• H.P. Williams, Model Building in Mathematical Programming, 4th edition. Wiley, 1993. A popular collection of optimization models and modeling techniques.

• W.L. Winston, Introduction to Mathematical Programming: Applications and Algorithms, 2nd edition. Wadsworth, 1997. A widely used elementary introduction to optimization topics.

Linear Programming

• D. Bertsimas and J. Tsitsiklis, Introduction to Linear Optimization. Athena Scientific, 1996.

• V. Chvatal, Linear Programming. W.H. Freeman & Co., 1983. A perennial favorite among introductory texts.

• S.I. Gass, An Illustrated Guide to Linear Programming. Dover, 1990. An inexpensive reprint of a classic introduction.

• I. Maros, Computational Techniques of the Simplex Method. Kluwer, 2003.

• R. Saigal, Linear Programming: A Modern Integrated Analysis. Kluwer, 1995.

• R.J. Vanderbei, Linear Programming: Foundations and Extensions, 2nd edition. Kluwer, 2001. An introductory graduate-level text covering theory and computation for both simplex and interior-point methods.

• S.J. Wright, Primal-Dual Interior-Point Methods. SIAM, 1997.

Nonlinear Programming

• M.S. Bazaraa, H.D. Sherali and C.M. Shetty, Nonlinear Programming: Theory and Algorithms. Wiley, 1992.

• D.P. Bertsekas, Nonlinear Programming. Athena Scientific, 1995.

• R. Fletcher, Nonlinear Programming, 2nd edition. Wiley, 2000.

• P.E. Gill, W. Murrary and M.H. Wright, Practical Optimization. Academic Press, 1981.

• D.G. Luenberger, Linear and Nonlinear Programming, 2nd edition. Addison-Wesley, 1984.

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

• J. Nocedal and S.J. Wright, Numerical Optimization. Springer Verlag, 1999.

Integer Programming and Combinatorial Optimization

• W.J. Cook, W.H. Cunningham, W.R. Pulleyblank and A. Schrijver, Combinatorial Optimization. Wiley Interscience, 1997. A comprehensive and up-to-date treatment.

• G.L. Nemhauser and L.A. Wolsey, Integer and Combinatorial Optimization. Wiley Interscience, 1988. An advanced text that covers many theortical and computational topics in integer programming.

• C.H. Papadimitriou and K. Steiglitz, Combinatorial Optimization: Algorithms and Complexity. Dover, 1998. Recently reprinted in an inexpensive paperback edition.

• L.A. Wolsey, Integer Programming. Wiley, 1998. An introduction to the subject and its applications.

Network Optimization

• R.K. Ahuja, T.L. Magnanti and J.B. Orlin, Network Flows: Theory, Algorithms, and Applications. Prentice-Hall, 1993. A comprehensive recent survey of the topic.

• D.P. Bertsekas, Linear Network Optimization: Algorithms and Codes. MIT Press, 1991. Includes code for a variety of network algorithms.

• D.P. Bertsekas, Network Optimization: Continuous and Discrete Models. Athena Scientific, 1998.

• K.G. Murty, Network Programming. Prentice-Hall, 1992.

Additional Topics of Interest

• D.P. Bertsekas and J. Tsitsiklis, Parallel and Distributed Computation: Numerical Methods. Athena Scientific, 1997.

• Y. Censor and S.A. Zenios, Parallel Optimization: Theory, Algorithms, and Applications. Oxford University Press, 1998. Winner of the 1999 INFORMS Computing Society Prize for Research Excellence in the Interface Between Operations Research and Computer Science.

• L.S. Lasdon, Optimization Theory for Large Systems. Dover, 2002. A survey of decomposition, relaxation, column-generation, and compact-basis methods for large-scale optimization, in an inexpensive reprint edition.

• K. Marriott and P.J. Stuckey, Programming With Constraints: An Introduction. MIT Press, 1998. An introduction to techniques that can provide an alternative to integer programming for highly combinatorial problems. (See also the proposed AMPL extensions that would take advantage of constraint logic programming solvers.)

• J.D. Pinter, Global Optimization in Action: Continuous and Lipschitz Optimization: Algorithms, Implementations and Applications. Kluwer, 1996. Winner of the 1999 INFORMS Computing Society Prize for Research Excellence in the Interface Between Operations Research and Computer Science.

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