# krainaksiazek modeling and solving linear programming with r 20097926

- znaleziono 9 produktów w 2 sklepach

### Linear Optimization Problems with Inexact Data Springer, Berlin

**Książki / Literatura obcojęzyczna**

Linear programming has attracted the interest of mathematicians since World War II when the first computers were constructed. Early attempts to apply linear programming methods practical problems failed, in part because of the inexactness of the data used to create the models. This book presents a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.Linear programming attracted the interest of mathematicians during and after World War II when the first computers were constructed and methods for solving large linear programming problems were sought in connection with specific practical problems for example, providing logistical support for the U.S. Armed Forces or modeling national economies. Early attempts to apply linear programming methods to solve practical problems failed to satisfy expectations. There were various reasons for the failure. One of them, which is the central topic of this book, was the inexactness of the data used to create the models. This phenomenon, inherent in most pratical problems, has been dealt with in several ways. At first, linear programming models used "average values of inherently vague coefficients, but the optimal solutions of these models were not always optimal for the original problem itself. Later researchers developed the stochastic linear programming approach, but this too has its limitations. Recently, interest has been given to linear programming problems with data given as intervals, convex sets and/or fuzzy sets. The individual results of these studies have been promising, but the literature has not presented a unified theory. Linear Optimization Problems with Inexact Data attempts to present a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.§Audience§This book is intended for postgraduate or graduate students in the areas of operations research, optimization theory, linear algebra, interval analysis, reliable computing, and fuzzy sets. The book will also be useful for researchers in these respective areas.

Sklep: Libristo.pl

### Linear Optimization Problems with Inexact Data Springer, Berlin

**Książki / Literatura obcojęzyczna**

Linear programming attracted the interest of mathematicians during and after World War II when the first computers were constructed and methods for solving large linear programming problems were sought in connection with specific practical problems for example, providing logistical support for the U.S. Armed Forces or modeling national economies. Early attempts to apply linear programming methods to solve practical problems failed to satisfy expectations. There were various reasons for the failure. One of them, which is the central topic of this book, was the inexactness of the data used to create the models. This phenomenon, inherent in most pratical problems, has been dealt with in several ways. At first, linear programming models used "average" values of inherently vague coefficients, but the optimal solutions of these models were not always optimal for the original problem itself. Later researchers developed the stochastic linear programming approach, but this too has its limitations. Recently, interest has been given to linear programming problems with data given as intervals, convex sets and/or fuzzy sets. The individual results of these studies have been promising, but the literature has not presented a unified theory. Linear Optimization Problems with Inexact Data attempts to present a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.

Sklep: Libristo.pl

### Optimization Modeling with Spreadsheets John Wiley & Sons Inc

**Książki / Literatura obcojęzyczna**

Thoroughly updated to reflect the latest topical and technical advances in the field, "Optimization Modeling with Spreadsheets, Third Edition" continues to focus on solving real-world optimization problems through the creation of mathematical models and the use of spreadsheets for analysis. Developed and extensively classroom-tested, the book features a systematic approach that equips readers with the skills needed to apply optimization tools effectively without the need to rely on specialized algorithms. This introductory book on optimization (mathematical programming) includes coverage on linear programming, nonlinear programming, integer programming, and heuristic programming, with an emphasis on model building using Excel's freely available Solver. The focus on model building (rather than algorithms) is one feature that makes this book distinctive as most books devote more space to algorithmic details than to formulation principles. These days, however, it is not necessary to know a great deal about algorithms in order to apply optimization tools, especially when relying on the spreadsheet as a solution platform. This emphasis on spreadsheets is another feature that makes this book distinctive. Few books devoted to optimization pay much attention to spreadsheet implementation of optimization principles, and most books that emphasize model building ignore spreadsheets entirely. To address the capabilities of sensitivity analysis, the use of Excel's Sensitivity Toolkit is employed. In addition, the book's past use of the Risk Solver Platform for Education (RSPE) is not completely abandoned as the author does include instructions on the use of RSPE for solving optimization problems within an appendix.

Sklep: Libristo.pl

### Primer in Biological Data Analysis and Visualization Using R University Press Group Ltd

**Książki / Literatura obcojęzyczna**

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.

Sklep: Libristo.pl

### Primer in Biological Data Analysis Using R University Press Group Ltd

**Książki / Literatura obcojęzyczna**

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.

Sklep: Libristo.pl

### New Trends in Nanotechnology and Fractional Calculus Springer Verlag

**Dla dzieci**

In recent years fractional calculus has played an important role in various fields such as mechanics, electricity, chemistry, biology, economics, modeling, identification, control theory and signal processing. The scope of this book is to present the state of the art in the study of fractional systems and the application of fractional differentiation. Furthermore, the manufacture of nanowires is important for the design of nanosensors and the development of high-yield thin films is vital in procuring clean solar energy. This wide range of applications is of interest to engineers, physicists and mathematicians.Table of contentsPreface;New trends in nanotechnology: Novel Molecular Diodes Developed by Chemial Conjugation of Carbon Nanotubes with Peptide Nucleic Acid, by Krishna V. Singh, Miroslav Penchev, Xiaoye Jing, Alfredo A. Martinez-Morales, Cengiz S. Ozkan and Mihri Ozkan;Hybrid Single Walled Carbon Nanotube FETs for High Fidelity DNA Detection, by Xu Wang, Mihri Ozkan, Gurer Budak, Ziya B. Guvenc and Cengiz S. Ozkan;Towards integrated nanoelectronic and photonic devices, by Alexander Quandt, Maurizio Ferrari and Giancarlo C. Righini;New noninvasive methods for

Sklep: Albertus.pl

### Optimization Concepts and Applications in Engineering Cambridge University Press

**Książki / Literatura obcojęzyczna**

It is vitally important to meet or exceed previous quality and reliability standards while at the same time reducing resource consumption. This textbook addresses this critical imperative integrating theory, modeling, the development of numerical methods and problem solving, thus preparing the student to apply optimization to real-world problems. This text covers a broad variety of optimization problems using: unconstrained, constrained, gradient and non-gradient techniques; duality concepts; multiobjective optimization; linear, integer, geometric and dynamic programming with applications; and finite element based optimization. In this revised and enhanced second edition of Optimization Concepts and Applications in Engineering, the already robust pedagogy has been enhanced with more detailed explanations, an increased number of solved examples and end-of-chapter problems. The source codes are now available free on multiple platforms. It is ideal for advanced undergraduate or graduate courses and for practising engineers in all engineering disciplines, as well as in applied mathematics.

Sklep: Libristo.pl

### Introduction to Quantitative Methods in Business Wiley & Sons

**Książki / Literatura obcojęzyczna**

A well-balanced and accessible introduction to elementary quantitative methods and Microsoft(r) Office Excel(r) applications used to guide business decision making§§Featuring quantitative techniques essential for modeling modern business situations, Introduction to Quantitative Methods in Business: With Applications Using Microsoft(r) Office Excel(r) provides guidance to assessing real-world data sets using Excel. The book presents a balanced approach to the mathematical tools and techniques, including applications, used in the areas of business, finance, economics, marketing, and operations.§§The authors begin by establishing a solid foundation of basic mathematics and statistics before moving on to more advanced concepts. The first part of the book starts by developing basic quantitative techniques such as arithmetic operations, functions and graphs, and elementary differentiations (rates of change), and integration. After a review of these techniques, the second part details both linear and nonlinear models of business activity. Extensively classroom-tested, Introduction to Quantitative Methods in Business: With Applications Using Microsoft(r) Office Excel(r) also includes:§Numerous examples and practice problems that emphasize real-world business quantitative techniques and applications§Excel-based computer software routines that explore calculations for an assortment of tasks, including graphing, formulae usage, solving equations, and data analysis§End-of-chapter sections detailing the Excel applications and techniques used to address data and solutions using large data sets§A companion website that includes chapter summaries, Excel data sets, sample exams and quizzes, lecture slides, and an Instructors' Solutions Manual§§Introduction to Quantitative Methods in Business: With Applications Using Microsoft(r) Office Excel(r) is an excellent textbook for undergraduate-level courses on quantitative methods in business, economics, finance, marketing, operations, and statistics. The book is also an ideal reference for readers with little or no quantitative background who require a better understanding of basic mathematical and statistical concepts used in economics and business.

Sklep: Libristo.pl

### Data Smart Wiley

**Książki / Literatura obcojęzyczna**

Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope. Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart , author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data. Each chapter will cover a different technique in a spreadsheet so you can follow along: Mathematical optimization, including non-linear programming and genetic algorithms Clustering via k-means, spherical k-means, and graph modularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, and bag-of-words models Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

Sklep: Libristo.pl

Sklepy zlokalizowane w miastach: Warszawa, Kraków, Łódź, Wrocław, Poznań, Gdańsk, Szczecin, Bydgoszcz, Lublin, Katowice

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