Linear Programming Computation

Linear Programming Computation  eBooks & eLearning

Posted by nebulae at April 13, 2014
Linear Programming Computation

Ping-Qi Pan, "Linear Programming Computation"
English | ISBN: 3642407536 | 2014 | 768 pages | PDF | 6 MB

Linear Programming: Algorithms and applications  eBooks & eLearning

Posted by lengen at Nov. 15, 2016
Linear Programming: Algorithms and applications

Linear Programming: Algorithms and applications
English | October 4, 2013 | ISBN: 0412164302 | 156 Pages | PDF | 3 MB

This text is based on a course of about 16 hours lectures to students of mathematics, statistics, and/or operational research. It is intended to introduce readers to the very wide range of applicability of linear programming, covering problems of manage­ ment, administration, transportation and a number of other uses which are mentioned in their context. The emphasis is on numerical algorithms, which are illustrated by examples of such modest size that the solutions can be obtained using pen and paper. It is clear that these methods, if applied to larger problems, can also be carried out on automatic (electronic) computers. Commercially available computer packages are, in fact, mainly based on algorithms explained in this book.

Linear Programming: Algorithms and applications  eBooks & eLearning

Posted by lengen at Nov. 15, 2016
Linear Programming: Algorithms and applications

Linear Programming: Algorithms and applications
English | October 4, 2013 | ISBN: 0412164302 | 156 Pages | PDF | 3 MB

This text is based on a course of about 16 hours lectures to students of mathematics, statistics, and/or operational research. It is intended to introduce readers to the very wide range of applicability of linear programming, covering problems of manage­ ment, administration, transportation and a number of other uses which are mentioned in their context. The emphasis is on numerical algorithms, which are illustrated by examples of such modest size that the solutions can be obtained using pen and paper. It is clear that these methods, if applied to larger problems, can also be carried out on automatic (electronic) computers. Commercially available computer packages are, in fact, mainly based on algorithms explained in this book.

Linear Programming and Generalizations: A Problem-based Introduction with Spreadsheets  eBooks & eLearning

Posted by ChrisRedfield at Nov. 28, 2015
Linear Programming and Generalizations: A Problem-based Introduction with Spreadsheets

Eric V. Denardo - Linear Programming and Generalizations: A Problem-based Introduction with Spreadsheets
Published: 2011-07-25 | ISBN: 1441964908 | PDF | 673 pages | 5.33 MB

Stochastic Linear Programming: Models, Theory, and Computation (repost)  eBooks & eLearning

Posted by arundhati at June 14, 2015
 Stochastic Linear Programming: Models, Theory, and Computation (repost)

Peter Kall, János Mayer, " Stochastic Linear Programming: Models, Theory, and Computation"
2011 | 2nd edition | ISBN-10: 1441977287 | 448 pages | PDF | 3 MB

Stochastic Linear Programming: Models, Theory, and Computation by János Mayer [Repost]  eBooks & eLearning

Posted by tanas.olesya at Jan. 28, 2015
Stochastic Linear Programming: Models, Theory, and Computation by János Mayer [Repost]

Stochastic Linear Programming: Models, Theory, and Computation (International Series in Operations Research & Management Science) by János Mayer
English | Feb 17, 2005 | ISBN: 0387233857 | 405 Pages | PDF | 16 MB

Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization.

Linear Programming and Extensions (Repost)  eBooks & eLearning

Posted by step778 at May 7, 2014
Linear Programming and Extensions (Repost)

George Dantzig, "Linear Programming and Extensions"
1963 | pages: 634 | ISBN: 0691080003 | PDF | 25,7 mb
Stochastic Linear Programming: Models, Theory, and Computation (2nd edition) (Repost)

Peter Kall, János Mayer - Stochastic Linear Programming: Models, Theory, and Computation (2nd edition)
Published: 2010-11-10 | ISBN: 1441977287 | PDF | 448 pages | 3 MB

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup.
Stochastic Linear Programming: Models, Theory, and Computation (2nd edition) (Repost)

Peter Kall, János Mayer - Stochastic Linear Programming: Models, Theory, and Computation (2nd edition)
Published: 2010-11-10 | ISBN: 1441977287 | PDF | 448 pages | 3 MB

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup.

Stochastic Linear Programming: Properties, Solution Methods, and Applications  eBooks & eLearning

Posted by spiderman at Nov. 27, 2006
Stochastic Linear Programming: Properties, Solution Methods, and Applications

Peter Kall, Janos Mayer, «Stochastic Linear Programming Properties, Solution Methods, and Applications»
Springer | ISBN 0387233857 | February 2005 | PDF | 416 Pages | 17,0 Mb

Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization. Stochastic Linear Programming: Models, Theory, and Computation is a definitive presentation and discussion of the theoretical properties of the models, the conceptual algorithmic approaches, and the computational issues relating to the implementation of these methods to solve problems that are stochastic in nature. The application area of stochastic programming includes portfolio analysis, financial optimization, energy problems, random yields in manufacturing, risk analysis, etc. In this book, models in financial optimization and risk analysis are discussed as examples, including solution methods and their implementation.