Compact Extended Linear Programming Models (euro Advanced Tutorials On Operational Research)
by Giuseppe Lancia /
2017 / English / PDF
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This book provides a handy, unified introduction to the theory of
compact extended formulations of exponential-size integer linear
programming (ILP) models. Compact extended formulations are equally
powerful, but polynomial-sized, models whose solutions do not
require the implementation of separation and pricing procedures.
The book is written in a general, didactic form, first developing
the background theoretical concepts (polyhedra, projections, linear
and integer programming) and then delving into the various
techniques for compact extended reformulations. The techniques are
illustrated through a wealth of examples touching on many
application areas, such as classical combinatorial optimization,
network design, timetabling, scheduling, routing, computational
biology and bioinformatics. The book is intended for graduate or
PhD students – either as an advanced course on selected topics or
within a more general course on ILP and mathematical programming –
as well as for practitioners and software engineers in industry
exploring techniques for developing optimization models for their
specific problems.
This book provides a handy, unified introduction to the theory of
compact extended formulations of exponential-size integer linear
programming (ILP) models. Compact extended formulations are equally
powerful, but polynomial-sized, models whose solutions do not
require the implementation of separation and pricing procedures.
The book is written in a general, didactic form, first developing
the background theoretical concepts (polyhedra, projections, linear
and integer programming) and then delving into the various
techniques for compact extended reformulations. The techniques are
illustrated through a wealth of examples touching on many
application areas, such as classical combinatorial optimization,
network design, timetabling, scheduling, routing, computational
biology and bioinformatics. The book is intended for graduate or
PhD students – either as an advanced course on selected topics or
within a more general course on ILP and mathematical programming –
as well as for practitioners and software engineers in industry
exploring techniques for developing optimization models for their
specific problems.