81. 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). http://www.informatik.uni-koeln.de/abacus/

impressum University of Cologne Faculty of Mathematics and Natural Sciences home download installation feedback ... literature news: ABACUS Version 3.0 now with Coin-OpenSolverInterface ABACUS - A Branch-And-CUt System ABACUS is a software system written in C++ that provides a framework for the implementation of branch-and-bound algorithms using linear programming relaxations. Cutting planes or columns can be generated dynamically (branch-and-cut, branch-and-price, branch-and-cut-and-price). ABACUS allows the software developer to concentrate merely on the problem specific parts, i.e., the separation of cutting planes, column generation, and primal heuristics. ABACUS supports the Open Solver Interface (Osi) developed by the COIN-OR (COmputational INfrastructure for Operations Research) project which means that every solver supported by OSI can be used to solve the relaxations. Moreover, ABACUS provides a variety of general algorithmic concepts, e.g., a list of different enumeration and branching strategies from which the best alternative for the user's application can be chosen.

82. Linear Programming - Math Central Natasha Glydon. Consider this scenario your school is planning to make toques and mitts to sell at the winter festival as a fundraiser. The school’s sewing classes divide http://mathcentral.uregina.ca/beyond/articles/LinearProgramming/linearprogram.ht

Math Central - mathcentral.uregina.ca Math Beyond School return to top Linear Programming Natasha Glydon Consider this scenario: In order to make the most money from the fundraiser, how many of each item should be made each week? It is important to understand that profit (the amount of money made from the fundraiser) is equal to the revenue (the total amount of money made) minus the costs: Proft = Revenue - Cost. Because the students are donating their time and the community is donating the material, the cost of making the toques and mitts is zero. So in this case, profit revenue If the quantity you want to optimize (here, profit) and the constraint conditions (more on them later) are linear, then the problem can be solved using a special organization called linear programming Creating equations, or inequalities, and graphing them can help solve simple linear programming problems, like the one above. We can assign variables to represent the information in the above problem. x = the number of toques made weekly y = the number of pairs of mitts made weekly Then, we can write linear inequalities based on the constraints from the problem.

83. Compuchem Consultants - Engineering Services, Software And IT Services For Petro Suppliers of engineering services, software products for linear programming modeling, and IT Services http://www.compuchem.net

/*********************************************** * Chrome CSS Drop Down Menu- (c) Dynamic Drive DHTML code library (www.dynamicdrive.com) * This notice MUST stay intact for legal use * Visit Dynamic Drive at http://www.dynamicdrive.com/ for full source code ***********************************************/ /*********************************************** * Step Carousel Viewer script- (c) Dynamic Drive DHTML code library (www.dynamicdrive.com) * Visit http://www.dynamicDrive.com for hundreds of DHTML scripts * This notice must stay intact for legal use ***********************************************/ Home About Engineering Services Software ... Plant Explorer cssdropdown.startchrome("chromemenu") Call: 1-949-733-9042 Compuchem Consultants World class services for process industries! Experienced consultants serving the Chemical Engineering and Manufacturing Industries. Testimonials for our software tools: “I must tell you that most people in our plant are very impressed ... I have been able to reduce a particular quality defect (edge cracks off the Hot Mill) by 78%. No one including myself has been able to do that in 20 years of operating this plant.” Golden Aluminum “… has been effectively used by IBM to rapidly model and optimize existing processes, as well as efficiently develop from zero knowledge high performance processes to standards not previously experienced... Final process yield improvement and process variability reduction are to be expected via this technology.”

84. Linear Programming - Formulation ORNotes 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). http://people.brunel.ac.uk/~mastjjb/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.

85. IBM - Mathematical Programs - IBM ILOG CPLEX Optimizer - Software Highperformance mathematical programming solver for linear programming, mixed integer programming, and quadratic programming http://www.ibm.com/software/integration/optimization/cplex-optimizer/

mboxCreate('software_global_top'); Skip to main content United States change Home Solutions Services ... IBM ILOG CPLEX Optimization Studio IBM ILOG CPLEX Optimizer High-performance mathematical programming solver for linear programming, mixed integer programming, and quadratic programming Overview Learn more System requirements Specifications sheet CPLEX performance Getting Started manual Model business issues mathematically and solve them with IBM ILOG CPLEX Optimizer's powerful algorithms to produce precise and logical decisions. IBM ILOG CPLEX Optimizer's mathematical programming technology enables analytical decision support for improving efficiency, reducing costs, and increasing profitability. Fundamental algorithms: IBM ILOG CPLEX Optimizer provides flexible, high-performance mathematical programming solvers for linear programming, mixed integer programming, quadratic programming, and quadratically constrained programming problems. Robust algorithms for demanding problems: IBM ILOG CPLEX Optimizer has solved problems with millions of constraints and variables. Industry-leading support: IBM has an impressive rate of product improvement and ample support resources to serve you.

86. Linear Programming Linear Programming Linear Programming is a particular case of constrained optimization problems. What sets the linear programming aside is that optimal values are sought for a http://www.cut-the-knot.org/do_you_know/lin_pr.shtml

87. IBM ILOG Optimization - Advanced Analytics And Analytical Decision Support Solut Optimization algorithms, resource allocation, resource optimization, tools to improve decision-making. http://www.ilog.com/products/optimization/

mboxCreate('software_global_top'); Skip to main content United States change Home Solutions Services ... WebSphere IBM ILOG Optimization and Analytical Decision Support Solutions Make smarter decisions, faster with optimization technology Why IBM? The gold standard in optimization software, technology and solutions, IBM ILOG Optimization is used by over 50% of the world's largest companies, 1000’s of Universities, and 1000's of application providers. The leader in optimization and performance , IBM ILOG Optimization solutions tackle the world's toughest problems allowing firms to gain a unique competitive advantage for a very wide range of optimization applications. IBM ILOG Supply Chain Optimization provides easy-to-use, optimization-based decision support solutions to solve complex supply chain and production problems. These off-the-shelf applications are used by over 50% of the world's largest supply chains and over 50% of AMR's top 50 global supply chains. What we offer Products IBM ILOG ODM Enterprise Enterprise-class software platform for building optimization-based custom planning and scheduling decision support applications. IBM ILOG CPLEX Optimization Studio Optimization model development toolkit for mathematical programming and constraint programming.

88. The Math Forum - Math Library - Linear Progrmng Operations research game theory and linear programming an online linear programming solver; and an online solver of two-person zero sum games (play a two-person zero sum game http://mathforum.org/library/topics/linear_prog/

Browse and Search the Library Home Math Topics Operations Research : Linear Progrmng Library Home Search Full Table of Contents Suggest a Link ... Library Help Selected Sites (see also All Sites in this category Game Theory, Linear/Non-Linear Programming - Math Forum Links to some of the best Internet resources for game theory and linear or non-linear programming: Web sites, software, Internet projects, publications, and public forums for discussion. more>> Linear Programming FAQ - Optimization Technology Center, Northwestern University and Argonne National Laboratory Posted monthly to the newsgroup sci.op-research. Answers to questions such as: "What is Linear Programming?" "Where is there a good code to solve LP problems?" "Oh, and we also want to solve it as an integer program." "I wrote an optimization code. Where are some test models?" "What is MPS format?" etc. more>> All Sites - 47 items found, showing 1 to 47 Academic OR/MS Courses on the Web - Armann Ingolfsson Links to Web pages of courses in Operations Research/Management Science and related fields offered at universities or colleges all over the world. Also short courses and tutorials on OR/MS-related topics. By Armann Ingolfsson for the INFORMS Forum on ...more>> AMPL: A Modeling Language for Mathematical Programming - Bell Laboratories A comprehensive and powerful algebraic modeling language for linear and nonlinear optimization problems, in discrete or continuous variables. AMPL lets you use common notation and familiar concepts to formulate optimization models and examine solutions

89. IBM - Mathematical Programs - IBM ILOG CPLEX Optimizer - Software The CPLEX division of ILOG provides large-scale mathematical programming software and services for resource optimization. http://www.ilog.com/products/cplex/

mboxCreate('software_global_top'); Skip to main content United States change Home Solutions Services ... IBM ILOG CPLEX Optimization Studio IBM ILOG CPLEX Optimizer High-performance mathematical programming solver for linear programming, mixed integer programming, and quadratic programming Overview Learn more System requirements Specifications sheet CPLEX performance Getting Started manual Model business issues mathematically and solve them with IBM ILOG CPLEX Optimizer's powerful algorithms to produce precise and logical decisions. IBM ILOG CPLEX Optimizer's mathematical programming technology enables analytical decision support for improving efficiency, reducing costs, and increasing profitability. Fundamental algorithms: IBM ILOG CPLEX Optimizer provides flexible, high-performance mathematical programming solvers for linear programming, mixed integer programming, quadratic programming, and quadratically constrained programming problems. Robust algorithms for demanding problems: IBM ILOG CPLEX Optimizer has solved problems with millions of constraints and variables. Industry-leading support: IBM has an impressive rate of product improvement and ample support resources to serve you.

90. Linear Programming Summary | BookRags.com Linear Programming. Linear Programming summary with 3 pages of encyclopedia entries, research information, and more. http://www.bookrags.com/research/linear-programming-wom/

91. SolvOpt: Index Page Matlab, C, and Fortran codes to minimize nonlinear, possibly non-smooth objective functions and solve nonlinear minimization problems, taking into account constraints by the method of exact penalization. http://www.uni-graz.at/imawww/kuntsevich/solvopt/

92. Home Software, benchmarks, events, people, bibliography, quadratic optimization. http://rutcor.rutgers.edu/~pbo/

The Pseudo-Boolean Optimization Website W elcome to the home page for the Pseudo-Boolean Optimization (PBO) web-project. What's New The following is a dated list of additions to our web. A bibliography on PBO has been added to this website. The family has been added to the set of benchmark problems. The list of best known values of the Large and the Medium families has been updated. Optimal values have been found for several benchmarks in families: D E OR-LIB 100 and OR-LIB 250 Due to an error in a script file, the OR-LIB 1000 benchmarks were incorrectly manipulated in the past. This problem is fixed now, and the best values of this dataset can be seen here unconstrained 0-1 quadratic test problems have been added to the set of benchmark problems. For each particular dataset, the best 0-1 vector solution found can be obtained in this website. The best known results for a set of benchmark problems for 0-1 quadratic optimization can be obtained here There are some test problems with new best values to the research community, namely within the and families.

93. Pseudo-Boolean (0-1 Integer Programming) Benchmarks With Hidden Optimum Solution Benchmarks in opb format. Includes a description of how they were generated. http://www.nlsde.buaa.edu.cn/~kexu/benchmarks/pb-benchmarks.htm

Pseudo-Boolean (0-1 Integer Programming) Benchmarks with Hidden Optimum Solutions If you have any comments or need more instances for the following benchmarks, please send me an email. The Pseudo-Boolean 0-1 integer programming ) problem is a linear integer programming problem where all variables are restricted to take values of either or 1. This problem is NP-hard, and as such, it is considered unlikely that there exists an efficient algorithm for solving it. The Pseudo-Boolean (0-1 Integer Programming) benchmarks presented here are transformed from forced satisfiable SAT benchmarks of Model RB, with the set of variables and the set of constraints respectively corresponding to the set of variables and the set of binary clauses in SAT instances. In fact, based on Model RB and this transformation, we can propose a simple random Pseudo-Boolean model as follows: First generate n disjoint sets of variables, each of which has cardinality n (where is a constant), and then for every two variables x and y in the same set, generate a constraint

94. Mosek: Home Large scale optimization software. Solves linear, quadratic, general convex and mixed integer optimization problems. Details of products, trial downloads, licensing information, and documentation. http://www.mosek.com/

Home Introduction Products Downloads ... advanced search The MOSEK Optimization Software The MOSEK Optimization Software is designed to solve large-scale mathematical optimization problems. MOSEK provides specialized solvers for linear programming, mixed integer programming and many types of nonlinear convex optimization problems. MOSEK can solve: Linear problems. Conic quadratic problems. Convex quadratic problems. General convex problems. Mixed integer problems. Interfaces included in MOSEK: Complete native interfaces for: C/C++ .NET Java and Python Optimization toolbox for MATLAB Technical highlights of MOSEK are: Both simplex and interior-point based optimizers are available. Can exploit multiple CPUs. For more information about MOSEK click here New to MOSEK If you are new to MOSEK, then we suggest you visit the introduction section Markowitz portfolio optimization using MOSEK. A new technical report is available that demonstrates how easy it is to use MOSEK for the Markowitz portfolio optimization problems even if transactions costs are included. Please consult our publications and grab a copy of the report.

95. Professor George Dantzig, Stanford Operations Research Department The versatility and economic impact of linear programming in today s The somewhat confusing name linear programming, Dantzig explained in the book, http://www.stanford.edu/group/SOL/dantzig.html

Home Software Personnel Students, Alumni, Visitors ... Systems Using SOL Publications Books Dissertations Journal Papers Classics ... Dantzig Memoriam In association with SCCM iCME Memorial Fellowships Dantzig-Lieberman Fund Gene Golub Fund Systems Optimization Laboratory Stanford University Terman Engineering Center Stanford, CA 94305-4026 USA Professor George Dantzig: Linear Programming Founder Turns 80 SIAM News, November 1994 In spite of impressive developments in computational optimization in the last 20 years, including the rapid advance of interior point methods, the simplex method, invented by George B. Dantzig in 1947, has stood the test of time quite remarkably: It is still the pre-eminent tool for almost all applications of linear programming. Dantzig, who turns 80 on November 8, is generally regarded as one of the three founders of linear programming, along with von Neumann and Kantorovich. Through his research in mathematical theory, computation, economic analysis, and applications to industrial problems, he has contributed more than any other researcher to the remarkable development of linear programming. Dantzig's work has been recognized by numerous honors, among them the National Medal of Science (1975), the John von Neumann Theory Prize of the Operations Research Society of America and the Institute of Management Sciences (1974), and membership in the National Academy of Sciences, the National Academy of Engineering, and the American Academy of Arts and Sciences. But he has his own basis for judging his work: "The final test of any theory," he said in the opening sentence of his 1963 book

96. Zuse-Institut Berlin: Optimierung, Optimierung Sequential object-oriented simplex class library, free to download for research purposes for members of non-commercial and academic institutions. http://www.zib.de/Optimization/Software/Soplex/

Kontakt Impressum Presse Sitemap ... English KONRAD-ZUSE-ZENTRUM BERLIN Institut Forschung Menschen Service Projektsite Zur Navigation springen Zum Inhalt springen Home Forschung ... Diskrete Mathematik Forschung Numerische Mathematik Diskrete Mathematik Optimierung Lineare und Nichtlineare Ganzzahlige Optimierung Telekommunikation Verkehr und Logistik Mitarbeiter ... Informatik Quicklinks News Mathematik-Kalender Projekte Spin-Offs ... Raumvergabe Quickview Optimierung Leitung: Prof. Dr. Dr. h.c. mult. Martin Grötschel Dr. habil. Ralf Borndörfer Mitarbeiter Projekte ( Aktuell Archiv Publikationen Software Optimierung Leitung Prof. Dr. Dr. h.c. mult. Martin Grötschel Dr. habil. Ralf Borndörfer Sekretariat Bettina Kasse Sylwia Markwardt Beschreibung Die inhaltlichen Schwerpunkte der Forschung und Entwicklung der Abteilung liegen v.a. in dem Bereich Algorithmische Diskrete Mathematik. Dabei werden eine Vielzahl theoretisch- oder praktisch orientierter Projekte bearbeitet, welche sich in folgende Themenkreise untergliedern lassen: Lineare und Nichtlineare Ganzzahlige Optimierung Telekommunikation Verkehr und Logistik monochrome Darstellung ... login

97. The Nonlinear Geometry Of Linear Programming I. Affine And File Format PDF/Adobe Acrobat Quick View http://www.math.lsa.umich.edu/~lagarias/doc/new.lin.pdf

98. Linear Optimization Linear programming deals with a class of optimization problems, where both the objective function to be optimized and all the constraints, are linear in terms of the decision http://home.ubalt.edu/ntsbarsh/Business-stat/opre/partVIII.htm

Deterministic Modeling: Linear Optimization with Applications Europe Site Site for Asia Site for Middle East UK Site ... USA Site Para mis visitantes del mundo de habla hispana,este sitio se encuentra disponible en espa�ol en: Versi�n en Espa�ol Sitio Espejo para Espa�a Sitio Espejo para Am�rica Latina A mathematical optimization model consists of an objective function and a set of constraints in the form of a system of equations or inequalities. Optimization models are used extensively in almost all areas of decision-making, such as engineering design and financial portfolio selection. This site presents a focused and structured process for optimization problem formulation, design of optimal strategy, and quality-control tools that include validation, verification, and post-solution activities. 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. " parameter " or " linear " If the first appearance of the word/phrase is not what you are looking for, try F ind Next MENU Optimization-Modeling Process Ingredients of Optimization Problems and Their Classification Linear Programming (LP) Dual Problem: Its Construction and Economics Implications ... Europe Mirror Site Companion Sites: Success Science Leadership Decision Making Linear Optimization Software to Download Artificial-variable Free LP Solution Algorithms ... Decision Science Resources Ingredients of Optimization Problems and Their Classification Introduction Bilevel Optimization Combinatorial Optimization Constraint Satisfaction ... Swarm Intelligence Linear Programming (LP)

99. HOPDM's Home Page Package for solving large-scale linear, convex quadratic and convex nonlinear programming problems. The code is an implementation of the infeasible primal-dual interior point method, and compares favorably with commercial LP, QP and NLP packages. http://www.maths.ed.ac.uk/~gondzio/software/hopdm.html

HOPDM is a package for solving large scale linear, convex quadratic and convex nonlinear programming problems. The code is an implementation of the infeasible primal-dual interior point method. It uses multiple centrality correctors; their number is chosen appropriately for a given problem in order to reduce the overall solution time. HOPDM automatically chooses the most efficient factorization method for a given problem (either normal equations or augmented system). The code compares favourably with commercial LP, QP and NLP packages. HOPDM has been written by Jacek Gondzio An extension for convex QP has been developed together with Anna Altman An extension for convex NLP has been developed together with Olivier Epelly (see NLPHOPDM A decomposition environment based on HOPDM has been developed together with Robert Sarkissian . It is called PDCGM which stands for Primal-Dual Column Generation Method. Special thanks go to Marek Makowski for help in a development of the C version of the code. HOPDM has been designed to satisfy two complementary goals: to offer its user a facility of building his own interior point based application; and

100. EE236A - Linear Programming (Fall 2007-08) EE236A Linear Programming (Fall 2007-08). Prof. L. Vandenberghe, UCLA Large-scale linear programming (4/page). Integer linear programming (4/page) http://www.ee.ucla.edu/ee236a/ee236a.html

EE236A - Linear Programming (Fall 2007-08) Prof. L. Vandenberghe , UCLA Lectures notes Introduction and overview 4/page Linear inequalities 4/page ... 4/page Homework Homework 1 (due 10/11): Exercises 2, 6, 8 (a,c,d,e,g), 9, 11. Homework 2 (due 10/18): Exercises 12, 14 (b), 15, 20, 36. Homework 3 (due 10/25): Exercises 22, 23, 26, 30, 31 (a). Homework 4 (due 11/1): Exercises 28, 29, 33, 40, 41. Homework 5 (due 11/8): Exercises 42, 44, 50, 53, 55. Homework 6 (due 11/15): Exercises 45, 54, 58, 63, 66. Homework 7 (due 11/29): Exercises 46, 47, 69, 71, 72, 74. Homework 8 (due 12/7): Exercises 75, 76, 86. Submit your code for problem 86 by email to vandenbe@ee.ucla.edu. The homework assignments are from the EE236A Exercises . Some of the problems require Matlab files: ex9data.m ex15data.m ex17data.m ex18data.m ... ex35data.m Software Matlab The Matlab LP solver is called linprog MOSEK linprog linprog . You can also use the routine lp236a.m , a pure Matlab implementation of a primal-dual method. This code is less efficient and reliable than the MOSEK solver, but should be adequate for the purposes of this course. The following Matlab packages allow you to specify and solve LPs using a very simple and intuitive description format: CVX (which includes the necessary solver) and YALMIP Octave Octave users can download the Octave version of lp236a.m

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