Data, Models, and Decisions: The Fundamentals of Management Science

The paperback version is only available for international sales only. This book represents a departure from existing textbooks. Rather than covering methodology, the book introduces decision support systems through real world applications, and uses spreadsheets to model and solve problems. It uses management science techniques (statistics, simulation, probabilistic modeling and optimization), but only as tools to facilitate problem solving. The book embraces George Dantzig's dictum as its premise: "The final test of any theory is its capacity to solve the problems which originated it." 
The book is used in the core MBA program at MIT's, Sloan School of Management for the class titled: "Data, Models and Decisions". It is used in over ten universities in both core and elective classes, including Stanford University, Chicago's graduate school of Business, Babson College, among several others. 
The book contains many real business cases from the authors consulting experience. There are Powerpoint presentation slides for lecture material, a solution manual and other instructor resources available that can be obtained by contacting the authors directly ( dbertsim@mit.edu , rfreund@mit.edu )

Business & Money

Dimitris Bertsimas

Robert Freund

Management & Leadership

Dynamic Ideas

The book provides a unified, insightful, and modern treatment of the theory of integer optimization. 
The book is used in the doctoral level course, "Integer and Combinatorial Optimization" at the Massachusetts Institute of Technology. 
For solutions to exercises and other instructor resources, please contact Dimitris Bertsimas (dbertsim@mit.edu). 
The chapters of the book are logically organized in four parts: 
Part I: Formulations and relaxations includes Chapters 1-5 and discusses how to formulate integer optimization problems, how to enhance the formulations to improve the quality of relaxations, how to obtain ideal formulations, the duality of integer optimization and how to solve the resulting relaxations both practically and theoretically. 
Part II: Algebra and geometry of integer optimization includes Chapters 6-8 and develops the theory of lattices, oulines ideas from algebraic geometry that have had an impact on integer optimization, and most importantly discusses the geometry of integer optimization, a key feature of the book. These chapters provide the building blocks for developing algorithms. 
Part III: Algorithms for integer optimization includes Chapters 9-12 and develops cutting plane methods, integral basis methods, enumerative and heuristic methods and approximation algorithms. The key characteristic of our treatment is that our development of the algorithms is naturally based on the algebraic and geometric developments of Part II. 
Part IV: Extensions of integer optimization includes Chapters 13 and 14, and treats mixed integer optimization and robust discrete optimization. Both areas are practically significant as real world problems have very often both continuous and discrete variables and have elements of uncertainty that need to be addressed in a tractable manner. 
Distinguishing Characteristics Of This Book: 
* Develops the theory of integer optimization from a new geometric perspective via integral generating sets; 
* Emphasizes strong formulations, ways to improve them, integral polyhedra, duality, and relaxations; 
* Discusses applications of lattices and algebraic geometry to integer optimization, including Grobner bases, optimization over polynomials and counting integer points in polyhedra; 
* Contains a unified geometric treatment of cutting plane and integral basis methods; 
* Covers enumerative and heuristic methods, including local search over exponential neighborhoods and simulated annealing; 
* Presents the major methods to construct approximation algorithms: primal-dual, randomized rounding, semidefinite and enumerative methods; 
* Provides a unified treatment of mixed integer and robust discrete optimization; 
* Includes a large number of examples and exercises developed through extensive classroom use.

Optimization Over Integers

Robert Weismantel

The book covers a wide variety of applied operations research in a way not seen elsewhere. With an emphasis on model building, not theorem proving, the book starts with a review applied probability and contains material on geometrical probability not easily accessible elsewhere. Spatial as well as temporal Poisson processes are covered in depth. Then the applied probability is put to good use in a chapter devoted to queueing models. This is a stand-alone introduction to queueing theory that may be useful in a variety of courses, just as the geometrical probability segment has stand-alone value. The next chapter is a unique tour of spatial queues, combining geometrical probability concepts with models of queues from previous chapters. The core of the chapter is development of the Hypercube Queueing model, a model that -- 31 years after its original development -- remains the gold standard in modeling municipal emergency services such as police, emergency medical and fire departments. The homework problems at the end of this chapter are the most challenging in the book, many worthy of the most advanced doctoral students. The book then shifts slightly from primarily probabilistic models to a combination of probabilistic and deterministic models, focusing on transportation networks analysis. This graph-focused chapter develops rigorous results by intuitive visual arguments, not abstract algebraic theorem proving. It too is a stand-alone chapter, the longest and most comprehensive in the book. There follows a brief chapter on the theory and mechanics of Monte Carlo simulation. This is good material even for people who use packaged simulation software, as it focuses on fundamentals and issues to think about even when using packaged software. The book concludes with a unique chapter on implementation, based on the personal experiences of the authors and their students in attempting to implement the models, methods and philosophies of the book.

Urban Operations Research

Politics & Social Sciences

Richard C. Larson

Amedeo R. Odoni

Politics & Government

Decision support systems combine models, data, and information technology for effective decision-making and are becoming increasingly popular in business and industry. Developing Web-Enabled Decision Support Systems is a comprehensive book that describes how to build data-driven, Web-enabled decision support systems using a Microsoft Access database, VB .NET, and an ASP .NET framework and illustrates it using several case studies arising in Management, Engineering, and Operations Research.

Developing Web-Enabled Decision Support Systems

Abhijit A. Pol

Ravindra K. Ahuja

A decision support system (DSS) is an intelligent information system that uses data, models it, processes or analyzes it using problem-specific methodologies, and assists the user in the decision-making process through a graphical user interface (GUI). Developing Spreadsheet-Based Decision Support Systems is a comprehensive book that describes how to build decision support systems using the Excel spreadsheet framework and the VBA programming language. This book illustrates complete decision support development applications through several case studies arising in operations research, industrial engineering, management, and business administration.

Developing Spreadsheet-Based Decision Support Systems

Wayne L. Winston

Michelle M.H. Seref

Ravindra A. Ahuja

Operations Strategy: Principles and Practice provides a unified framework for operations strategy. The book shows how to tailor the operational system to maximize value and competitive advantage. Conceptual thinking and financial optimization yield guidelines for implementation. This dual emphasis on principles and practice is reflected by analytical models that are illustrated with detailed examples and a dozen case studies of real business situations.

Operations Strategy: Principles and Practice

Jan A. Van Mieghem

Principles of Supply Chain Management provides a succinct, focused treatment of supply chain management. The three-part structure provides a cohesive framework for the study of the subject. An up-front emphasis on both the connection of the supply chain to the organization and the significance of information technology facilitates quick engagement of students. Students gain the wherewithal to become problem solvers by learning to employ a combination of analysis and intuition in business decision-making.

Principles of Supply Chain Management

Scott Webster

STRUCTURE OF THE BOOK: Part I describes single and multi-server queues. Part II treats single and multiclass queueing networks (MQNETs). Part III introduces asymptotic methods, including queueing networks in heavy traffic, large deviations, call centers, queues in space, and the supermarket model. Part IV outlines the use of optimization in queueing networks. Part V presents Markov chains and processes, Brownian motion, and weak convergence in the Appendix.

Queueing Theory: Classical and Modern Methods

David Gamarnik

See the best price to sell, buy or rent books by the Dynamic Ideas publisher. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Dynamic Ideas