Business Optimization Using Mathematical Programming
Business Optimization Using Mathematical Programming Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Business Optimization Using Mathematical Programming book. This book definitely worth reading, it is an incredibly well-written.
Business Optimization Using Mathematical Programming by Josef Kallrath Pdf
This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.
Business Optimisation Using Mathematical Programming by Josef Kallrath,John M. Wilson Pdf
This new textbook provides a theoretical and practical introduction to Business Optimisation using mathematical programming. Few textbooks have integrated modelling with state-of-the-art commercially available software. This text will be up to date with relevant examples and cases and will be accompanied by the software to solve the models. An instructor's manual will also be available.
This book serves as an introductory text in mathematical programming and optimization for students having a mathematical background that includes one semester of linear algebra and a complete calculus sequence. It includes computational examples to aid students develop computational skills.
Mathematical Programming by Mik Wisniewski,Tony Dacre Pdf
This text focuses on a particular group of management science models, known collectively as mathematical programming, and the potential application of such models to business problems and decision-making.
Linear Optimization for Business by Marcos Singer Pdf
This book takes a unique approach to linear optimization by focusing on the underlying principles and business applications of a topic more often taught from a mathematical and computational perspective. By shifting the perspective away from heavy math, students learn how optimization can be used to drive decision making in real world business settings. The book does not shy away from the theory underlying linear optimization but rather focuses on ensuring students understand the logic without getting caught up in proving theorems. Plenty of examples, applications and case studies are included to help bridge the gap between the theory and the way it plays out in practice. The author has also included several Excel spreadsheets, showing worked-out models of linear optimization that have been used to drive decisions ranging from configuring a police force to purchasing crude oil and media planning. How can the routes and pricing structures of airlines be optimized? How much should be invested in the prevention and punishment of crimes? These are everyday problems that can be solved using linear optimization, and this book shows students just how to do that. It will prove a useful, math-free resource for all students of management science and operations research.
Optimization for Profit by Filmore E. Bender,Gerald Kahan,W. Charles Mylander Pdf
This major new volume provides business decisionmakers and analysts with a tool that provides a logical structure for understanding problems as well as a mathematical technique for solving them. The primary tool presented throughout Optimization for Profit is linear programming (LP)--a medium that can be mastered by any individual who seeks to improve his/her analytical and decisionmaking skills. One of the special features of Optimization for Profit is the illustration of activity analysis as the technique used to formulate problems. By using activity analysis as the problem structure, linear programming become a natural extension of the way decision makers approach problems. As a result, linear programming becomes an integral part of the thinking process of the individual. Consequently, students or practitioners can readily create a linear programming model of an entire business or any part of a business. Several chapters are devoted to describing this technique and illustrating its application to many different types of companies, including an oil refinery, a marmalade production company, and a chicken processing plant. A thorough study of Optimization for Profit will enable you to work with any manufacturer or service industry and model all or part of the operation, and then solve the model to determine how best to minimize costs or maximize profits. Many firms save hundreds of thousands of dollars each year through the application of linear programming. The authors have presented the material in this vital book so clearly and thoroughly that an individual could master the material through self-study. The inclusion of problems at the end of each chapter makes this book suitable as a textbook at the advanced undergraduate or beginning graduate level at most colleges or universities for students of management science, operations research personnel, and applied mathematicians working in industry, government, or academia. Notable features of the book include: the practical aspects of modeling a business or any part of a business using linear programming a unique approach to explain the simplex method for solving linear programming problems real life, practical problems that are presented and solved in detail detailed instructions for those interested in solving linear programming problems on all types of computers from mainframes to PCs numerous problems provided for the benefit of the student and all of the linear programming models described in these problems as well as in the text itself are available on a diskette
Introduction to Mathematical Programming by Russell C. Walker Pdf
Intended for Mathematical Programming courses at the undergraduate level. Course can be found in business schools-especially MBA programs-as Management Science and Operations Research. Providing the background in mathematics departments, the course may also be called Linear Programming or Optimization. Necessary to begin using mathematical programming as a tool for managerial applications and beyond, this empowering guide helps students learn to recognize when a mathematical model can be useful and helps them develop an appreciation and understanding of the mathematics associated with the applied techniques. Formatted in a flexible framework to suit individual course needs, it presents self-contained chapters later in the book which are designed to work in the order an instructor deems most suitable. For more information, please visit: http://www.math.cmu.edu/~rw1k/
Business Analytics for Decision Making by Steven Orla Kimbrough,Hoong Chuin Lau Pdf
Business Analytics for Decision Making, the first complete text suitable for use in introductory Business Analytics courses, establishes a national syllabus for an emerging first course at an MBA or upper undergraduate level. This timely text is mainly about model analytics, particularly analytics for constrained optimization. It uses implementations that allow students to explore models and data for the sake of discovery, understanding, and decision making. Business analytics is about using data and models to solve various kinds of decision problems. There are three aspects for those who want to make the most of their analytics: encoding, solution design, and post-solution analysis. This textbook addresses all three. Emphasizing the use of constrained optimization models for decision making, the book concentrates on post-solution analysis of models. The text focuses on computationally challenging problems that commonly arise in business environments. Unique among business analytics texts, it emphasizes using heuristics for solving difficult optimization problems important in business practice by making best use of methods from Computer Science and Operations Research. Furthermore, case studies and examples illustrate the real-world applications of these methods. The authors supply examples in Excel®, GAMS, MATLAB®, and OPL. The metaheuristics code is also made available at the book's website in a documented library of Python modules, along with data and material for homework exercises. From the beginning, the authors emphasize analytics and de-emphasize representation and encoding so students will have plenty to sink their teeth into regardless of their computer programming experience.
Nonlinear Optimization Applications Using the GAMS Technology by Neculai Andrei Pdf
Here is a collection of nonlinear optimization applications from the real world, expressed in the General Algebraic Modeling System (GAMS). The concepts are presented so that the reader can quickly modify and update them to represent real-world situations.
Approaches to mathematical optimization and its applications by Zamrooda Jabeen,Farida Khursheed Pdf
Doctoral Thesis / Dissertation from the year 2015 in the subject Mathematics - Applied Mathematics, , language: English, abstract: This book comprises various optimality criteria, duality and mixed duality in a variety of mathematical programming, that includes nondifferentiable nonlinear programming problems, nondifferentiable nonlinear fractional programming problems, nondifferentiable minimax fractional programming problems etc. Mathematical Programming is concerned with the determination of a minimum or maximum of a function of several variables, which are required to satisfy a number of constraints. Such solutions are sought are sought in diverse fields, including Engineering, Operations Research, Management Science and Economics. Often these situations are mathematical representations of certain real world problems, and hence are turned as mathematical programming problems. Optimality criteria and duality have played an important role in the development of mathematical programming. Optimality conditions were first investigated by Fritz John and later on, independently by Karush and Kuhn – Tucker. The inception of duality theory in linear programming may be traced to the classical minmax theorem of Von Neumann, which was subsequently formulated in a precise form by Gale, Kuhn and Tucker. Since then optimality criteria and duality have remained as one of the most widely investigated area in mathematical programming. Karush-Kuhn-Tucker conditions not only laid down the foundations for many computational techniques in mathematical programming, but also are a great deal responsible for the development of the duality theory. An extensive use of duality in mathematical programming has been made for many theoretical and computational developments in mathematical programming itself, economics, control theory, business problems and many other diverse fields. It is well known that duality principle connects two programs, one of which, called the Primal problem, is a constrained maximization (or minimization) problem, and the other one called the Dual, is a constrained minimization (or maximization) problem, in such a way that the existence of an optimal solution to one of them guarantees an optimal solution to the other and optimal values of the two problems are equal. A pair of dual problems is called symmetric if the dual of the dual is the primal itself.
An Introduction to Optimization by Edwin K. P. Chong,Stanislaw H. Żak Pdf
A modern, up-to-date introduction to optimization theory and methods This authoritative book serves as an introductory text to optimization at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization, Second Edition helps students build a solid working knowledge of the field, including unconstrained optimization, linear programming, and constrained optimization. Supplemented with more than one hundred tables and illustrations, an extensive bibliography, and numerous worked examples to illustrate both theory and algorithms, this book also provides: * A review of the required mathematical background material * A mathematical discussion at a level accessible to MBA and business students * A treatment of both linear and nonlinear programming * An introduction to recent developments, including neural networks, genetic algorithms, and interior-point methods * A chapter on the use of descent algorithms for the training of feedforward neural networks * Exercise problems after every chapter, many new to this edition * MATLAB(r) exercises and examples * Accompanying Instructor's Solutions Manual available on request An Introduction to Optimization, Second Edition helps students prepare for the advanced topics and technological developments that lie ahead. It is also a useful book for researchers and professionals in mathematics, electrical engineering, economics, statistics, and business. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology by Neculai Andrei Pdf
This book presents the theoretical details and computational performances of algorithms used for solving continuous nonlinear optimization applications imbedded in GAMS. Aimed toward scientists and graduate students who utilize optimization methods to model and solve problems in mathematical programming, operations research, business, engineering, and industry, this book enables readers with a background in nonlinear optimization and linear algebra to use GAMS technology to understand and utilize its important capabilities to optimize algorithms for modeling and solving complex, large-scale, continuous nonlinear optimization problems or applications. Beginning with an overview of constrained nonlinear optimization methods, this book moves on to illustrate key aspects of mathematical modeling through modeling technologies based on algebraically oriented modeling languages. Next, the main feature of GAMS, an algebraically oriented language that allows for high-level algebraic representation of mathematical optimization models, is introduced to model and solve continuous nonlinear optimization applications. More than 15 real nonlinear optimization applications in algebraic and GAMS representation are presented which are used to illustrate the performances of the algorithms described in this book. Theoretical and computational results, methods, and techniques effective for solving nonlinear optimization problems, are detailed through the algorithms MINOS, KNITRO, CONOPT, SNOPT and IPOPT which work in GAMS technology.
Matheuristics by Vittorio Maniezzo,Thomas Stützle,Stefan Voß Pdf
Metaheuristics support managers in decision-making with robust tools that provide high-quality solutions to important applications in business, engineering, economics, and science in reasonable time frames, but finding exact solutions in these applications still poses a real challenge. However, because of advances in the fields of mathematical optimization and metaheuristics, major efforts have been made on their interface regarding efficient hybridization. This edited book will provide a survey of the state of the art in this field by providing some invited reviews by well-known specialists as well as refereed papers from the second Matheuristics workshop to be held in Bertinoro, Italy, June 2008. Papers will explore mathematical programming techniques in metaheuristics frameworks, and especially focus on the latest developments in Mixed Integer Programming in solving real-world problems.
