A reference for those working at the interface of operations
planning and optimization modeling, Operations Planning: Mixed
Integer Optimization Models blends essential theory and powerful
approaches to practical operations planning problems. It presents a
set of classical optimization models with widespread application in
operations planning. The discussion of each of these classical
models begins with the motivation for studying the problem as well
as examples of the problem's application in operations planning
contexts. The book explores special structural results and
properties of optimal solutions that have led to effective
algorithmic solution approaches for each problem class. Each of the
models and solution methods presented is the result of high-impact
research that has been published in the scholarly literature, with
appropriate references cited throughout the book. The author
highlights the close relationships among the models, examining
those situations in which a particular model results as a special
case of other related models or how one model generalizes another.
Understanding these relationships allows you to more easily
characterize new models being developed through their relationships
to classical models. The models and methods presented in the book
have widespread application in operations planning. It enables you
to recognize the structural similarities between models and to
recognize these structural elements within other contexts. It also
gives you an understanding of various critical operations research
techniques and classical operations planning models, without the
need to consult numerous sources.
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