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 François
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).