Decomposition Techniques In Mathematical Programming: Engineering And Science Applications
by Enrique Castillo /
2010 / English / PDF
4.1 MB Download
Optimization plainly dominates the design, planning, operation, and
c- trol of engineering systems. This is a book on optimization that
considers particular cases of optimization problems, those with a
decomposable str- ture that can be advantageously exploited. Those
decomposable optimization problems are ubiquitous in engineering
and science applications. The book considers problems with both
complicating constraints and complicating va- ables, and analyzes
linear and nonlinear problems, with and without in- ger variables.
The decomposition techniques analyzed include Dantzig-Wolfe,
Benders, Lagrangian relaxation, Augmented Lagrangian decomposition,
and others. Heuristic techniques are also considered. Additionally,
a comprehensive sensitivity analysis for characterizing the
solution of optimization problems is carried out. This material is
particularly novel and of high practical interest. This book is
built based on many clarifying, illustrative, and compu- tional
examples, which facilitate the learning procedure. For the sake of
cl- ity, theoretical concepts and computational algorithms are
assembled based on these examples. The results are simplicity,
clarity, and easy-learning. We feel that this book is needed by the
engineering community that has to tackle complex optimization
problems, particularly by practitioners and
researchersinEngineering,OperationsResearch,andAppliedEconomics.The
descriptions of most decomposition techniques are available only in
complex and specialized mathematical journals, di?cult to
understand by engineers. A book describing a wide range of
decomposition techniques, emphasizing problem-solving, and
appropriately blending theory and application, was not previously
available.
Optimization plainly dominates the design, planning, operation, and
c- trol of engineering systems. This is a book on optimization that
considers particular cases of optimization problems, those with a
decomposable str- ture that can be advantageously exploited. Those
decomposable optimization problems are ubiquitous in engineering
and science applications. The book considers problems with both
complicating constraints and complicating va- ables, and analyzes
linear and nonlinear problems, with and without in- ger variables.
The decomposition techniques analyzed include Dantzig-Wolfe,
Benders, Lagrangian relaxation, Augmented Lagrangian decomposition,
and others. Heuristic techniques are also considered. Additionally,
a comprehensive sensitivity analysis for characterizing the
solution of optimization problems is carried out. This material is
particularly novel and of high practical interest. This book is
built based on many clarifying, illustrative, and compu- tional
examples, which facilitate the learning procedure. For the sake of
cl- ity, theoretical concepts and computational algorithms are
assembled based on these examples. The results are simplicity,
clarity, and easy-learning. We feel that this book is needed by the
engineering community that has to tackle complex optimization
problems, particularly by practitioners and
researchersinEngineering,OperationsResearch,andAppliedEconomics.The
descriptions of most decomposition techniques are available only in
complex and specialized mathematical journals, di?cult to
understand by engineers. A book describing a wide range of
decomposition techniques, emphasizing problem-solving, and
appropriately blending theory and application, was not previously
available.