Linear and integer optimization: theory and practice (Record no. 204675)

000 -LEADER
fixed length control field 07246cam a22002417i 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 150709b2015 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781498710169
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.72
Item number S4L4
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sierksma, Gerard
9 (RLIN) 74550
245 10 - TITLE STATEMENT
Title Linear and integer optimization: theory and practice
250 ## - EDITION STATEMENT
Edition statement 3rd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Boca Raton
Name of publisher, distributor, etc CRC Press
Date of publication, distribution, etc 2015
300 ## - PHYSICAL DESCRIPTION
Extent xxix, 684 p.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Advances in applied mathematics
9 (RLIN) 336606
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Table of Contents:<br/><br/>Basic Concepts of Linear Optimization<br/>The Company Dovetail<br/>Definition of an LO-Model<br/>Alternatives of the Standard LO-Model <br/>Solving LO-Models Using a Computer Package <br/>Linearizing Nonlinear Functions<br/>Examples of Linear Optimization Models<br/>Building and Implementing Mathematical Models <br/>Exercises<br/><br/>LINEAR OPTIMIZATION THEORY: BASIC TECHNIQUES<br/><br/>Geometry and Algebra of Feasible Regions<br/>The Geometry of Feasible Regions<br/>Algebra of Feasible Regions; Feasible Basic Solutions<br/>Exercises<br/><br/>Dantzig’s Simplex Algorithm<br/>From Vertex to Vertex to an Optimal Solution <br/>LO-Model Reformulation <br/>The Simplex Algorithm<br/>Simplex Tableaus<br/>Discussion of the Simplex Algorithm<br/>Initialization<br/>Uniqueness and Multiple Optimal Solutions<br/>Models with Equality Constraints<br/>The Revised Simplex Algorithm<br/>Exercises<br/><br/>Duality, Feasibility, and Optimality<br/>The Companies Dovetail and Salmonnose<br/>Duality and Optimality<br/>Complementary Slackness Relations<br/>Infeasibility and Unboundedness; Farkas’ Lemma<br/>Primal and Dual Feasible Basic Solutions<br/>Duality and the Simplex Algorithm<br/>The Dual Simplex Algorithm<br/>Exercises<br/><br/>Sensitivity Analysis<br/>Sensitivity of Model Parameters<br/>Perturbing Objective Coefficients<br/>Perturbing Right Hand Side Values (Nondegenerate Case)<br/>Piecewise Linearity of Perturbation Functions<br/>Perturbation of the Technology Matrix<br/>Sensitivity Analysis for the Degenerate Case<br/>Shadow Prices and Redundancy of Equality Constraints <br/>Exercises<br/><br/>Large-Scale Linear Optimization<br/>The Interior Path<br/>Formulation of the Interior Path Algorithm <br/>Convergence to the Interior Path; Maintaining Feasibility<br/>Termination and Initialization<br/>Exercises<br/><br/>Integer Linear Optimization<br/>Introduction<br/>The Branch-and-Bound Algorithm<br/>Linearizing Logical Forms with Binary Variables<br/>Gomory’s Cutting-Plane Algorithm<br/>Exercises<br/><br/>Linear Network Models<br/>LO-Models with Integer Solutions; Total Unimodularity<br/>ILO-Models with Totally Unimodular Matrices<br/>The Network Simplex Algorithm<br/>Exercises<br/><br/>Computational Complexity<br/>Introduction to Computational Complexity<br/>Computational Aspects of Dantzig’s Simplex Algorithm <br/>The Interior Path Algorithm Has Polynomial Running Time <br/>Computational Aspects of the Branch-and-Bound Algorithm <br/>Exercises<br/><br/>LINEAR OPTIMIZATION PRACTICE: ADVANCED TECHNIQUES<br/><br/>Designing a Reservoir for Irrigation<br/>The Parameters and the Input Data<br/>Maximizing the Irrigation Area<br/>Changing the Input Parameters of the Model <br/>GMPL Model Code <br/>Exercises<br/><br/>Classifying Documents by Language<br/>Machine Learning<br/>Classifying Documents Using Separating Hyperplanes<br/>LO-Model for Finding Separating Hyperplane<br/>Validation of a Classifier<br/>Robustness of Separating Hyperplanes; Separation Width <br/>Models that Maximize the Separation Width<br/>GMPL Model Code<br/>Exercises<br/><br/>Production Planning; A Single Product Case<br/>Model Description<br/>Regular Working Hours<br/>Overtime<br/>Allowing Overtime and Idle Time<br/>Sensitivity Analysis<br/>GMPL Model Code<br/>Exercises<br/><br/>Production of Coffee Machines<br/>Problem Setting<br/>An LO-Model that Minimizes Backlogs<br/>Old and Recent Backlogs<br/>Full Week Productions<br/>Sensitivity Analysis<br/>GMPL Model Code<br/>Exercises<br/><br/>Conflicting Objectives: Producing Versus Importing<br/>Problem Description and Input Data<br/>Modeling Two Conflicting Objectives; Pareto Optimal Point<br/>Goal Optimization for Conflicting Objective<br/>Soft and Hard Constraints<br/>Sensitivity Analysis<br/>Alternative Solution Techniques<br/>A Comparison of the Solutions<br/>GMPL Model Code<br/>Exercises<br/><br/>Coalition Formation and Profit Distribution<br/>The Farmers Cooperation Problem <br/>Game Theory; Linear Production Games <br/>How to Distribute the Total Profit Among the Farmers? <br/>Profit Distribution for Arbitrary Numbers of Farmers<br/>Sensitivity Analysis <br/>Exercises<br/><br/>Minimizing Trimloss When Cutting Cardboard<br/>Formulating the Problem <br/>Gilmore-Gomory’s Solution Algorithm<br/>Calculating an Optimal Solution<br/>Exercises<br/><br/>Off-Shore Helicopter Routing<br/>Problem Description<br/>Vehicle Routing Problems<br/>Problem Formulation <br/>ILO Formulation<br/>Column Generation<br/>Dual Values as Price Indicators for Crew Exchanges <br/>A Round-Off Procedure for Determining an Integer Solution <br/>Computational Experiments <br/>Sensitivity Analysis <br/>Exercises<br/><br/>The Catering Service Problem<br/>Formulation of the Problem <br/>The Transshipment Problem Formulation<br/>Applying the Network Simplex Algorithm <br/>Sensitivity Analysis<br/>GMPL Model Code<br/>Exercises<br/><br/>Appendix A Mathematical Proofs<br/>Appendix B Linear Algebra<br/>Appendix C Graph Theory<br/>Appendix D Convexity<br/>Appendix E Nonlinear Optimization<br/>Appendix F Writing LO-Models in GNU MathProg (GMPL)
520 ## - SUMMARY, ETC.
Summary, etc Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig’s simplex algorithm, duality, sensitivity analysis, integer optimization models, and network models are introduced.<br/>More advanced topics also are presented including interior point algorithms, the branch-and-bound algorithm, cutting planes, complexity, standard combinatorial optimization models, the assignment problem, minimum cost flow, and the maximum flow/minimum cut theorem.<br/>The second part applies theory through real-world case studies. The authors discuss advanced techniques such as column generation, multiobjective optimization, dynamic optimization, machine learning (support vector machines), combinatorial optimization, approximation algorithms, and game theory.<br/>Besides the fresh new layout and completely redesigned figures, this new edition incorporates modern examples and applications of linear optimization. The book now includes computer code in the form of models in the GNU Mathematical Programming Language (GMPL). The models and corresponding data files are available for download and can be readily solved using the provided online solver.<br/>This new edition also contains appendices covering mathematical proofs, linear algebra, graph theory, convexity, and nonlinear optimization. All chapters contain extensive examples and exercises. This textbook is ideal for courses for advanced undergraduate and graduate students in various fields including mathematics, computer science, industrial engineering, operations research, and management science.<br/><br/>https://www.crcpress.com/Linear-and-Integer-Optimization-Theory-and-Practice-Third-Edition/Sierksma-Zwols/p/book/9781498710169
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Linear programming
9 (RLIN) 393
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Integer programming
9 (RLIN) 37299
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical optimization
9 (RLIN) 9798
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zwols, Yori
Relator term Author
9 (RLIN) 336607
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Advances in applied mathematics
9 (RLIN) 336606
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent location Current location Shelving location Date acquired Source of acquisition Cost, normal purchase price Item location Total Checkouts Total Renewals Full call number Barcode Date last seen Date last borrowed Cost, replacement price Koha item type
          Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library General Stacks 04/10/2016 12 4899.09 Slot 1682 (2 Floor, East Wing) 1 3 519.72 S4L4-2015 192908 28/04/2020 01/03/2020 6123.87 Books

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