Applied Integer Programming (ePub)

An accessible treatment of the modeling and solution of integer
programming problems, featuring modern applications and
software

In order to fully comprehend the algorithms associated with
integer programming, it is important to understand not only
how algorithms work, but also why they work.
Applied Integer Programming features a unique emphasis on
this point, focusing on problem modeling and solution using
commercial software. Taking an application-oriented approach, this
book addresses the art and science of mathematical modeling related
to the mixed integer programming (MIP) framework and discusses the
algorithms and associated practices that enable those models to be
solved most efficiently.

The book begins with coverage of successful applications,
systematic modeling procedures, typical model types, transformation
of non-MIP models, combinatorial optimization problem models, and
automatic preprocessing to obtain a better formulation. Subsequent
chapters present algebraic and geometric basic concepts of linear
programming theory and network flows needed for understanding
integer programming. Finally, the book concludes with classical and
modern solution approaches as well as the key components for
building an integrated software system capable of solving
large-scale integer programming and combinatorial optimization
problems.

Throughout the book, the authors demonstrate essential concepts
through numerous examples and figures. Each new concept or
algorithm is accompanied by a numerical example, and, where
applicable, graphics are used to draw together diverse problems or
approaches into a unified whole. In addition, features of solution
approaches found in today's commercial software are identified
throughout the book.

Thoroughly classroom-tested, Applied Integer Programming
is an excellent book for integer programming courses at the
upper-undergraduate and graduate levels. It also serves as a
well-organized reference for professionals, software developers,
and analysts who work in the fields of applied mathematics,
computer science, operations research, management science, and
engineering and use integer-programming techniques to model and
solve real-world optimization problems.