Column Generation [electronic resource] /
Desaulniers, Guy.editor.
Desrosiers, Jacques.editor.
Solomon, Marius M.editor.
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).
Description based upon print version of record.
Includes bibliographical references.
A Primer in Column Generation -- Shortest Path Problems with Resource Constraints -- Vehicle Routing Problem with Time Windows -- Branch-and-Price Heuristics: A Case Study on the Vehicle Routing Problem with Time Windows -- Cutting Stock Problems -- Large-Scale Models in the Airline Industry -- Robust Inventory Ship Routing by Column Generation -- Ship Scheduling with Recurring Visits and Visit Separation Requirements -- Combining Column Generation and Lagrangian Relaxation -- Dantzig-Wolfe Decomposition for Job Shop Scheduling -- Applying Column Generation to Machine Scheduling -- Implementing Mixed Integer Column Generation.
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).
Operations research.
Decision making.
Management science.
Mathematical optimization.
Computer mathematics.
Production management.
Mathematical models.
Operations Research/Decision Theory.
Operations Research, Management Science.
Optimization.
Computational Mathematics and Numerical Analysis.
Operations Management.
Mathematical Modeling and Industrial Mathematics.