Column Generation is an insightful overview of the state-of-the-art
in integer programming column generation and its many applications.
The volume begins with "A Primer in Column Generation" which
outlines the theory and ideas necessary to solve large-scale
practical problems, illustrated with a variety of examples. Other
chapters follow this introduction on "Shortest Path Problems with
Resource Constraints," "Vehicle Routing Problem with Time Window,"
"Branch-and-Price Heuristics," "Cutting Stock Problems," each
dealing with methodological aspects of the field. Three chapters
deal with transportation applications: "Large-scale Models in the
Airline Industry," "Robust Inventory Ship Routing by Column
Generation," and "Ship Scheduling with Recurring Visits and Visit
Separation Requirements." Production is the focus of another three
chapters: "Combining Column Generation and Lagrangian Relaxation,"
"Dantzig-Wolfe Decomposition for Job Shop Scheduling," and
"Applying Column Generation to Machine Scheduling." The final
chapter by FranAois Vanderbeck, "Implementing Mixed Integer Column
Generation," reviews how to set-up the Dantzig-Wolfe reformulation,
adapt standard MIP techniques to the column generation context
(branching, preprocessing, primal heuristics), and deal with
specific column generation issues (initialization, stabilization,
column management strategies).
The book is the first systematic treatment of column generation
methodologies. It will provide students, researchers, and
experienced column generation users with a much-needed
state-of-the-art survey of the field.
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