David J. Rader 
Deterministic Operations Research 
Models and Methods in Linear Optimization

Uniquely blends mathematical theory and algorithm design for
understanding and modeling real-world problems

Optimization modeling and algorithms are key components to
problem-solving across various fields of research, from operations
research and mathematics to computer science and engineering.
Addressing the importance of the algorithm design process.
Deterministic Operations Research focuses on the design of
solution methods for both continuous and discrete linear
optimization problems. The result is a clear-cut resource for
understanding three cornerstones of deterministic operations
research: modeling real-world problems as linear optimization
problem; designing the necessary algorithms to solve these
problems; and using mathematical theory to justify algorithmic
development.

Treating real-world examples as mathematical problems, the
author begins with an introduction to operations research and
optimization modeling that includes applications form sports
scheduling an the airline industry. Subsequent chapters discuss
algorithm design for continuous linear optimization problems,
covering topics such as convexity. Farkas’ Lemma, and the
study of polyhedral before culminating in a discussion of the
Simplex Method. The book also addresses linear programming duality
theory and its use in algorithm design as well as the Dual Simplex
Method. Dantzig-Wolfe decomposition, and a primal-dual interior
point algorithm. The final chapters present network optimization
and integer programming problems, highlighting various specialized
topics including label-correcting algorithms for the shortest path
problem, preprocessing and probing in integer programming, lifting
of valid inequalities, and branch and cut algorithms.

Concepts and approaches are introduced by outlining examples
that demonstrate and motivate theoretical concepts. The accessible
presentation of advanced ideas makes core aspects easy to
understand and encourages readers to understand how to think about
the problem, not just what to think. Relevant historical summaries
can be found throughout the book, and each chapter is designed as
the continuation of the ‘story’ of how to both model
and solve optimization problems by using the specific
problems-linear and integer programs-as guides. The book’s
various examples are accompanied by the appropriate models and
calculations, and a related Web site features these models along
with Maple(TM) and MATLAB® content for the discussed
calculations.

Thoroughly class-tested to ensure a straightforward, hands-on
approach, Deterministic Operations Research is an excellent
book for operations research of linear optimization courses at the
upper-undergraduate and graduate levels. It also serves as an
insightful reference for individuals working in the fields of
mathematics, engineering, computer science, and operations research
who use and design algorithms to solve problem in their everyday
work.

About the author

David J. Rader Jr., Ph D, is Associate Professor of Mathematics at Rose-Hulman Institute of Technology, where he is also the editor of the Rose-Hulman Institute of Technology Undergraduate Mathematics Journal. Dr. Rader currently focuses his research in the areas of nonlinear 0-1 optimization, computational integer programming, and exam time timetabling.