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Model Building in Mathematical Programming

Model Building in Mathematical Programming
Author: H. P. Williams
Publisher: John Wiley & Sons
Total Pages: 376
Release: 1985
Genre: Mathematical models
ISBN:

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This extensively revised and updated edition discusses the general principles of model building in mathematical programming and shows how they can be applied by using twenty simplified, but practical problems from widely different contexts. Suggested formulations and solutions are given in the latter part of the book, together with some computational experience to give the reader some feel for the computational difficulty of solving that particular type of model.


Model Building in Mathematical Programming

Model Building in Mathematical Programming
Author: H. P. Williams
Publisher: John Wiley & Sons
Total Pages: 376
Release: 1985
Genre: Mathematical models
ISBN:

Download Model Building in Mathematical Programming Book in PDF, ePub and Kindle

This extensively revised and updated edition discusses the general principles of model building in mathematical programming and shows how they can be applied by using twenty simplified, but practical problems from widely different contexts. Suggested formulations and solutions are given in the latter part of the book, together with some computational experience to give the reader some feel for the computational difficulty of solving that particular type of model.


Model Building in Mathematical Programming

Model Building in Mathematical Programming
Author: H. Paul Williams
Publisher: Milton, Australia : Jacaranda Press ; Oxford : B. Blackwell ; Toronto : J. Wiley
Total Pages: 376
Release: 1999-10-25
Genre: Business & Economics
ISBN:

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Review of previous editions 'Such a text - and this is the only one of this type I know of - should be the basis of all instruction in Mathematical Programming.' Journal of the Royal Statistical Society 'An excellent introduction ... for students of business administration and people who want to see the utility of operations research.' European Journal of Operational Research 'It will be appreciated very much by practitioners who already have knowledge in the field of mathematical programming.' Mathematical Programming Society Newsletter Model Building in Mathematical Programming Fourth Edition H. Paul Williams Faculty of Mathematical Studies, University of Southampton, UK This extensively revised fourth edition of this well-known and much praised book contains a great deal of new material. In particular sections and new problems have been added covering Revenue Management. Hydro Electric Generation, Date Envelopment (efficiency) Analysis, Milk Distribution and Collection and Constraint Programming. The book discusses the general principles of model building in mathematical programming and shows how they can be applied by using simplified but practical problems from widely different contexts. Suggested formulations and solutions are given in the latter part of the book together with computational experience to give the reader a feel for the computation difficulty of solving that particular type of model. Aimed at undergraduates, postgraduates, research students and managers, this book illustrates the scope and limitations of mathematical programming, and shows how it can be applied to real situations. By emphasizing the importance of the building and interpretation of models rather than the solution process, the author attempts to fill a gap left by the many works which concentrate on the algorithmic side of the subject.


Building and Solving Mathematical Programming Models in Engineering and Science

Building and Solving Mathematical Programming Models in Engineering and Science
Author: Enrique Castillo
Publisher: John Wiley & Sons
Total Pages: 568
Release: 2011-10-24
Genre: Mathematics
ISBN: 0471461652

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Fundamental concepts of mathematical modeling Modeling is one of the most effective, commonly used tools in engineering and the applied sciences. In this book, the authors deal with mathematical programming models both linear and nonlinear and across a wide range of practical applications. Whereas other books concentrate on standard methods of analysis, the authors focus on the power of modeling methods for solving practical problems-clearly showing the connection between physical and mathematical realities-while also describing and exploring the main concepts and tools at work. This highly computational coverage includes: * Discussion and implementation of the GAMS programming system * Unique coverage of compatibility * Illustrative examples that showcase the connection between model and reality * Practical problems covering a wide range of scientific disciplines, as well as hundreds of examples and end-of-chapter exercises * Real-world applications to probability and statistics, electrical engineering, transportation systems, and more Building and Solving Mathematical Programming Models in Engineering and Science is practically suited for use as a professional reference for mathematicians, engineers, and applied or industrial scientists, while also tutorial and illustrative enough for advanced students in mathematics or engineering.


Modelling in Mathematical Programming

Modelling in Mathematical Programming
Author: José Manuel García Sánchez
Publisher: Springer Nature
Total Pages: 291
Release: 2020-10-31
Genre: Business & Economics
ISBN: 3030572501

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This book provides basic tools for learning how to model in mathematical programming, from models without much complexity to complex system models. It presents a unique methodology for the building of an integral mathematical model, as well as new techniques that help build under own criteria. It allows readers to structure models from the elements and variables to the constraints, a basic modelling guide for any system with a new scheme of variables, a classification of constraints and also a set of rules to model specifications stated as logical propositions, helping to better understand models already existing in the literature. It also presents the modelling of all possible objectives that may arise in optimization problems regarding the variables values. The book is structured to guide the reader in an orderly manner, learning of the components that the methodology establishes in an optimization problem. The system includes the elements, which are all the actors that participate in the system, decision activities that occur in the system, calculations based on the decision activities, specifications such as regulations, impositions or actions of defined value and objective criterion, which guides the resolution of the system.


Methods and Models in Mathematical Programming

Methods and Models in Mathematical Programming
Author: S. A. MirHassani
Publisher: Springer Nature
Total Pages: 389
Release: 2019-12-09
Genre: Mathematics
ISBN: 3030270459

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This book focuses on mathematical modeling, describes the process of constructing and evaluating models, discusses the challenges and delicacies of the modeling process, and explicitly outlines the required rules and regulations so that the reader will be able to generalize and reuse concepts in other problems by relying on mathematical logic.Undergraduate and postgraduate students of different academic disciplines would find this book a suitable option preparing them for jobs and research fields requiring modeling techniques. Furthermore, this book can be used as a reference book for experts and practitioners requiring advanced skills of model building in their jobs.


Modeling Languages in Mathematical Optimization

Modeling Languages in Mathematical Optimization
Author: Josef Kallrath
Publisher: Springer Science & Business Media
Total Pages: 427
Release: 2013-12-01
Genre: Mathematics
ISBN: 1461302153

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This volume presents a unique combination of modeling and solving real world optimization problems. It is the only book which treats systematically the major modeling languages and systems used to solve mathematical optimization problems, and it also provides a useful overview and orientation of today's modeling languages in mathematical optimization. It demonstrates the strengths and characteristic features of such languages and provides a bridge for researchers, practitioners and students into a new world: solving real optimization problems with the most advances modeling systems.


Logic and Integer Programming

Logic and Integer Programming
Author: H. Paul Williams
Publisher: Springer Science & Business Media
Total Pages: 167
Release: 2009-04-09
Genre: Computers
ISBN: 0387922806

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Paul Williams, a leading authority on modeling in integer programming, has written a concise, readable introduction to the science and art of using modeling in logic for integer programming. Written for graduate and postgraduate students, as well as academics and practitioners, the book is divided into four chapters that all avoid the typical format of definitions, theorems and proofs and instead introduce concepts and results within the text through examples. References are given at the end of each chapter to the more mathematical papers and texts on the subject, and exercises are included to reinforce and expand on the material in the chapter. Methods of solving with both logic and IP are given and their connections are described. Applications in diverse fields are discussed, and Williams shows how IP models can be expressed as satisfiability problems and solved as such.


Practical Time Series Analysis

Practical Time Series Analysis
Author: Aileen Nielsen
Publisher: O'Reilly Media
Total Pages: 500
Release: 2019-09-20
Genre: Computers
ISBN: 1492041629

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Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance