1. Linear Programming: Foundations And Extensions linear programming Foundations and Extensions. Book Cover Image Order. Table of Contents. Lecture Presentations for Chapters 2, 5, 13 http://www.princeton.edu/~rvdb/LPbook/

Linear Programming: Foundations and Extensions Order Table of Contents Lecture Presentations for Chapters 13 (intro) , and 13 (algorithms) (pdf format) (Note: the embedded hyperlinks work best if the pdf file is downloaded and viewed using acroread rather than a web browser; i.e., right-click is better than left-click.) Lecture Notes-Undergraduate level (pdf format) Lecture Notes-Graduate level (pdf format) Online version of 2nd Edition (note that the hyperlinks in the text really work) Associated software (C/C++ source code) Additional Exercises Online Exercises Errata Simple pivot tool (a java applet to help solve exercises from Chapters 1 to 5) Advanced pivot tool (a java applet to help solve exercises from Chapters 5 to 7) Online pivot exam (a java applet to evaluate your knowledge of the simplex method) The Network-Simplex Pivot Tool Intended Audience This book is an introductory graduate textbook on linear programming although upper-level graduate students and researchers will find plenty of material here that cannot be found in other books. It has also been used successfully to teach undergraduates majoring in Operations Research.

2. Optimization Frequently Asked Questions Includes basic definitions and links to free and commercial software. http://www-unix.mcs.anl.gov/otc/Guide/faq/

Optimization Frequently Asked Questions Linear Programming FAQ Nonlinear Programming FAQ These FAQs were established by John W. Gregory and are currently being maintained by Robert Fourer 4er@iems.nwu.edu ) and the Optimization Technology Center of Argonne National Laboratory and Northwestern University. NEOS Guide NEOS Server Comments

3. Linear Programming FAQ linear programming Frequently Asked Questions. Optimization Technology Center of application areas. Q1. What is linear programming? . A (For http://www-unix.mcs.anl.gov/otc/Guide/faq/linear-programming-faq.html

Linear Programming Frequently Asked Questions Optimization Technology Center of Northwestern University and Argonne National Laboratory Posted at http://www-unix.mcs.anl.gov/otc/Guide/faq/linear-programming-faq.html Changes posted to Usenet newsgroup sci.op-research Date of this version: April 1, 2004 What is Linear Programming Where is there good software to solve LP problems?" "Free" codes Commercial codes and modeling systems Free demos of commercial codes Q3. "Oh, and we also want to solve it as an integer program Q4. "I wrote an optimization code. Where are some test models Q5. "What is MPS format Topics briefly covered: : "What is a modeling language?" : "How do I diagnose an infeasible LP model?" : "I want to know the specific constraints that contradict each other." : "I just want to know whether or not a feasible solution exists : "I have an LP, except it's got several objective functions." : "I have an LP that has large almost-independent matrix blocks that are linked by a few constraints. Can I take advantage of this?" : "I am looking for an algorithm to compute the convex hull of a finite number of points in n-dimensional space."

4. An Introduction To Linear Programming And The Simplex Algorithm next Next The LP formulation and. An Introduction to linear programming and the Simplex Algorithm. by Spyros Reveliotis. Acknowledgements. http://www.isye.gatech.edu/~spyros/LP/LP.html

Next: The LP formulation and An Introduction to Linear Programming and the Simplex Algorithm by Spyros Reveliotis Acknowledgements There are a number of people who have contributed during the inceptional and implementational phases of this project through constructive comments and discussions, provision of information and technical assistance. At this point, I would like to acknowledge their valuable aid. Hence, I would like to say a "big" THANKS to: Evangelia Dimaraki, Amy Pritchett, Bhaskar Manda, Darren Hunt, Victoria Burse, Randy Riegsecker, Balu Vandor, Javier Ruiz and Fangjun Zhou . Many thanks go also to my students of the past IE3231 classes , since it was my interaction with them that motivated and inspired this whole effort. I would also like to acknowledge the financial (and not only) support of the School of Industrial and Systems Engineering and the CETL group at the Georgia Institute of Technology The integrated software supporting the execution of interactive examples "re-uses" the very nice software modules developed by (i) Drs Ken Goldberg and Ilan Adler at the Dept. of Industrial Engineering and Operations Research

5. Linear Programming Faq http//wwwunix.mcs.anl.gov/otc/Guide/ faq/linear-programming-faq.html. Please update your links. http://www.mcs.anl.gov/home/otc/Guide/faq/linear-programming-faq.html

This page has moved to http://www-unix.mcs.anl.gov/otc/Guide/faq/linear-programming-faq.html Please update your links.

6. Linear Programming Short Course Web sites with materials for linear programming, supporting the linear programming Short Course. Computer Society has named the simplex method of linear programming one of the top 10 algorithms http://www.cudenver.edu/~hgreenbe/courseware/LPshort/intro.html

7. Mathematics Archives - Topics In Mathematics - Linear/Nonlinear Programming Linear / Nonlinear programming. Optimization. Advanced linear programming. ADD. KEYWORDS Sensitivity Analysis, Model AnimaLP A Tool for Teaching linear programming Another Copy http://archives.math.utk.edu/topics/linearProg.html

Topics in Mathematics Linear / Nonlinear Programming Optimization Advanced Linear Programming ADD. KEYWORDS: Sensitivity Analysis, Model Simplification, Graphs of Linear Programs, Embedded and Hidden Structures, Sparse Matrix Techniques for Simplex and Interior Methods, Course Notes AMS's Materials Organized by Mathematical Subject Classification - Economics, Operations Research, Programming, Games ADD. KEYWORDS: Electronic Journals, Preprints, Web Sites, Databases AMS's Materials Organized by Mathematical Subject Classification ADD. KEYWORDS: Electronic Journals, Preprints, Web Sites, Databases AMS's Materials Organized by Mathematical Subject Classification ADD. KEYWORDS: Electronic Journals, Preprints, Web Sites, Databases Anima-LP: A Tool for Teaching Linear Programming Another Copy Annals of Operations Research ADD. KEYWORDS: Published Journal Bibliography on Interior Point Methods for Mathematical Programming CCC - Constraints Archive ADD. KEYWORDS: People, Bibliographies, Papers, Software, Benchmarks

8. Linear Programming Frequently Asked Questions linear programming Frequently Asked Questions This list is maintained by Robert Fourer and the Optimization Technology Center of Northwestern University and Argonne National Laboratory. Posted http://rdre1.inktomi.com/click?u=http://www-unix.mcs.anl.gov/otc/Guide/faq/linea

9. ABACUS ABACUS is a software system which provides a framework for the implementation of branchand-bound algorithms using linear programming relaxations that can be complemented with the dynamic generation of cutting planes or columns (branch-and-cut, branch-and-price,branch-and-cut-and-price). http://www.informatik.uni-koeln.de/ls_juenger/projects/abacus.html

ABACUS - A Branch-And-CUt System ABACUS is a software system which provides a framework for the implementation of branch-and-bound algorithms using linear programming relaxations that can be complemented with the dynamic generation of cutting planes or columns (branch-and-cut, branch-and-price, branch-and-cut-and-price). This system allows the software developer to concentrate merely on the problem specific parts, i.e., the cutting plane and column generation and the primal heuristics. Moreover, ABACUS provides a variety of general algorithmic concepts, e.g., enumeration and branching strategies, from which the user of the system can choose the best alternative for his application. Finally, ABACUS provides many basic data structures and useful tools for the implementation of such algorithms. ABACUS is designed both for general mixed integer optimization problems and for combinatorial optimization problems. It unifies cutting plane and column generation within one algorithm framework. Simple reuse of code and the design of abstract data structures and algorithms are essential for a software framework. These requirements are met by object oriented programming techniques. Therefore, ABACUS is implemented as a collection of C++ classes. Distributions ABACUS is distributed as a callable library together with an example and the documentation. We provide precompiled libraries for various UNIX platforms and Windows NT. The current version of ABACUS is release 2.2.

10. Optimization Frequently Asked Questions linear programming FAQ. Nonlinear programming FAQ. These FAQs were established by John W. Gregory and are currently being maintained by Robert Fourer ( http://www.mcs.anl.gov/home/otc/Guide/faq

Optimization Frequently Asked Questions Linear Programming FAQ Nonlinear Programming FAQ These FAQs were established by John W. Gregory and are currently being maintained by Robert Fourer 4er@iems.nwu.edu ) and the Optimization Technology Center of Argonne National Laboratory and Northwestern University. NEOS Guide NEOS Server Comments

11. QSopt Linear Programming Solver It can also be used as a standalone code to solve large-scale linear programming problems. David Applegate, William Cook, Sanjeeb Dash, and Monika Mevenkamp. http://www.isye.gatech.edu/~wcook/qsopt/

qs_doc_start('QSopt'); qs_doc_headline("QSopt Linear Programming Solver"); qs_body_start(true); The main purpose of QSopt is to provide a callable function library for use within applications such as the travelling salesman problem or mixed-integer-programming. It can also be used as a stand-alone code to solve large-scale linear programming problems. David Applegate William Cook Sanjeeb Dash , and Monika Mevenkamp Research supported by Office of Naval Research Grant N00014-03-1-0040. qs_doc_finish("March 2004");

12. Linear Programming FAQ linear programming FAQ. There are reader questions on this topic! Help others by sharing your knowledge Fourer) Newsgroups sci.opresearch Subject linear programming FAQ Date 1 Nov 1997 2255 http://www.cis.ohio-state.edu/hypertext/faq/usenet/linear-programming-faq/faq.ht

Usenet FAQs Search Web FAQs Documents ... RFC Index Linear Programming FAQ There are reader questions on this topic! Help others by sharing your knowledge From: 4er@iems.nwu.edu (Robert Fourer) Newsgroups: sci.op-research 4er@iems.nwu.edu (Robert Fourer) Summary: A List of Frequently Asked Questions about Linear Programming Keywords: FAQ, LP, Linear Programming Posted-By: auto-faq 2.4 Archive-name: linear-programming-faq Last-modified: November 1, 1997 [ ] Linear Programming Frequently Asked Questions Optimization Technology Center of Northwestern University and Argonne National Laboratory [ ] Posted monthly to Usenet newsgroup sci.op-research World Wide Web version: http://www.mcs.anl.gov/home/otc/Guide/faq/linear-programming-faq.html michel@es.ele.tue.nl ) says has solved models with up to 30,000 variables and 50,000 constraints. The author requests that people retrieve it from ftp://ftp.es.ele.tue.nl/pub/lp_solve (numerical address at last check: 131.155.20.126). There is an older version to be found in the Usenet archives, but it contains bugs that have been fixed in the meantime, and hence is unsupported. The author also made available a program that converts data files from MPS-format into lp_solve's own input format; it's in the same directory, in file mps2eq_0.2.tar.Z. The documentation states that it is not public domain, and the author wants to discuss it with would-be commercial users. As an editorial opinion, I must state that difficult models will give lp_solve trouble; it's not as good as a commercial code. But for someone who isn't sure what kind of LP code is needed, it represents a reasonable first try. LP-Optimizer is a simplex-based code for linear and integer programs, written by Markus Weidenauer (

13. Linear Programming linear programming This applet lets students experiment graphically with the value of linear functions of the form f(x y) = ax + by + c subject to linear constraints on x and y. Up to six linear http://rdre1.inktomi.com/click?u=http://exploremath.com/activities/Activity_page

14. Linear And Nonlinear Programming FAQs The FAQs for linear programming and Nonlinear programming have moved to a different site http//www.mcs.anl.gov/home/otc/Guide/faq/. http://www.skypoint.com/~ashbury/linear-programming-faq.html

The FAQs for Linear Programming and Nonlinear Programming have moved to a different site: http://www.mcs.anl.gov/home/otc/Guide/faq/

15. Linear Programming Language Information on LPL, a mathematical modeling language, related product, projects and links. http://diufpc03.unifr.ch/lpl/highl.html

16. Myths And Counterexamples back soon. linear programming; Mixed Integer Programming; Nonlinear programming. linear programming LP Min cx x = 0, Ax = b. x is http://www.cudenver.edu/~hgreenbe/myths/myths.html

You have reached http://www.cudenver.edu/~hgreenbe/myths/myths.html Myths and Counterexamples in Mathematical Programming by Harvey J. Greenberg This has counterexamples to some mathematical statements that seem plausible. It serves as useful teaching material, and is referenced by my Mathematical Programming Glossary Comments and/or contributions welcome (click on my name). The following categories will expand, so come back soon. Linear Programming Mixed Integer Programming Nonlinear Programming Linear Programming x is a column n-vector, c is a row n-vector, A is m by n matrix, b is column m-vector. Redundancy Break points Dual price Max flow = Min cut ... Jump to beginning Myth LP-1. All redundant constraints can be removed. Click here for explanation. Myth LP-2. direction of the RHS change. Then, z is piece-wise linear, where the break-points occur wherever there must be a basis change. Click here for explanation. Myth LP-3. Suppose LP is solved and p(i) is the dual price associated with the i-th constraint, A(i,.)x = b(i). Then, the same solution is obtained when removing the constraint and adding p(i)A(i,.)x to the objective. Click here for explanation.

17. Linear Programming - Formulation linear programming formulation. You will recall from the Two Mines example that the conditions for a mathematical model to be a linear program (LP) were http://mscmga.ms.ic.ac.uk/jeb/or/lp.html

OR-Notes J E Beasley OR-Notes are a series of introductory notes on topics that fall under the broad heading of the field of operations research (OR). They were originally used by me in an introductory OR course I give at Imperial College. They are now available for use by any students and teachers interested in OR subject to the following conditions A full list of the topics available in OR-Notes can be found here Linear programming - formulation You will recall from the Two Mines example that the conditions for a mathematical model to be a linear program (LP) were: all variables continuous (i.e. can take fractional values) a single objective (minimise or maximise) the objective and constraints are linear i.e. any term is either a constant or a constant multiplied by an unknown. LP's are important - this is because: many practical problems can be formulated as LP's there exists an algorithm (called the simplex algorithm) which enables us to solve LP's numerically relatively easily. We will return later to the simplex algorithm for solving LP's but for the moment we will concentrate upon formulating LP's.

18. Topics In Linear Algebra An approach unifying the notions of system of equations, matrix inversion, and linear programming. http://home.ubalt.edu/ntsbarsh/opre640a/partXII.htm

Unification of System of Linear Equations, Matrix Inversion, and Linear Programming Asia-Pacific Mirror Site Europe Mirror Site USA Site This site extends the existing one-way connections among the solving linear systems of equations, matrix inversion, and linear programming. The additional linkages empower the user to understand the wholeness and manifoldness of these topics. They also assist the user to model and solve a problem modeled as any one of the above topics by having access to a computer package solver. The goals are theoretical unification as well as advancements in applications. Illustrative numerical examples are presented. Professor Hossein Arsham To search the site , try E F ind in page [Ctrl + f]. Enter a word or phrase in the dialogue box, e.g. " inverse" or " equations" If the first appearance of the word/phrase is not what you are looking for, try F ind Next MENU Introduction LP Problem Solved by System of Equation Solver System of Equations Solution by LP Solver Solving for the Inverse of a Matrix Using LP Solver ... References and Further Readings Companion Sites: Success Science Asia-Pacific Mirror Site Europe Mirror Site Versión en Español ... Europe Mirror Site Introduction Linear programming (LP), Linear systems of equations, and Matrix inversion are often favorite topics for both instructors and students. The ability to solve these problems by Gauss-Jordan pivoting (GJP), the widespread availability of software packages, and their wide range of applications make these topics accessible even for students with relatively weak mathematical backgrounds. The typical textbooks on LP usually devote separate sections for each topic. However, the relationships among these closely related topics are often not presented or thoroughly discussed. This article extends the existing one-way connections among these topics to construct a comprehensive two-way relationship as in the following figure. For each topic, it is shown how the problem may be modeled and solved by either of the associated methodologies.

19. OR/MS Today - LINEAR PROGRAMMING SOFTWARE SURVEY 2003 linear programming. SOFTWARE SURVEY. The information in this survey was provided by the vendors in response to a questionnaire developed by Robert Fourer. Algorithms linear programming (Primal Simplexbased, Dual Simplex-based, Interior-point), Integer Programming http://lionhrtpub.com/orms/surveys/LP/LP-survey.html

OR/MS Today 2001 LINEAR PROGRAMMING SOFTWARE SURVEY The information in this survey was provided by the vendors in response to a questionnaire developed by Robert Fourer. The survey should not be considered as comprehensive, but rather as a representation of available Linear Programming packages. Questionnaires were sent to 60 vendors drawn from previous survey participants, the OR/MS Today database and other sources. It includes the products of those vendors who responded by July 1, 2001. If you know of a Linear Programming package that is not in this survey, please contact Jennie Farnsworth at (770) 431-0867, ext. 225 or e-mail them to jen@lionhrtpub.com . They will be included in the online version. The survey is broken down into nine separate tables (plus a vendor contact list) for easier downloading and viewing: Table 1: Software Description: Type: Form: Independent Application, Callable Library, Source Code, Add-in to General-purpose Software Table 2: Platforms Supported: DOS, PC/Windows (95, 97, NT), LINUX, UNIX, Mac OS, Other (specify) Multiprocessor Support: Shared Memory, Distributed Memory

20. Linear Programming - Solution here. linear programming solution. To get in solution technology. Some other linear programming solution examples can be found here. http://mscmga.ms.ic.ac.uk/jeb/or/solvelp.html

OR-Notes J E Beasley OR-Notes are a series of introductory notes on topics that fall under the broad heading of the field of operations research (OR). They were originally used by me in an introductory OR course I give at Imperial College. They are now available for use by any students and teachers interested in OR subject to the following conditions A full list of the topics available in OR-Notes can be found here Linear programming - solution To get some insight into solving LP's consider the Two Mines problem that we had before - the LP formulation of the problem was: Since there are only two variables in this LP problem we have the graphical representation of the LP given below with the feasible region (region of feasible solutions to the constraints associated with the LP) outlined. all feasible solutions to the original inequality constraint (e.g. all We determine the optimal solution to the LP by plotting (180x + 160y) = K (K constant) for varying K values (iso-profit lines). One such line (180x + 160y = 180) is shown dotted on the diagram. The smallest value of K (remember we are considering a minimisation problem) such that 180x + 160y = K goes through a point in the feasible region is the value of the optimal solution to the LP (and the corresponding point gives the optimal values of the variables). Hence we can see that the optimal solution to the LP occurs at the vertex of the feasible region formed by the intersection of 3x + y = 8 and 4x + 6y = 24. Note here that it is

Page 1     1-20 of 136    1  | 2  | 3  | 4  | 5  | 6  | 7  | Next 20