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Constraint Programming-based Column Generation
by
Malucelli, Federico
, Gualandi, Stefano
in
Algorithms
/ Business and Management
/ Column packings
/ Combinatorial analysis
/ Combinatorics
/ Decomposition
/ Flexibility
/ Graph coloring
/ Labeling
/ Linear programming
/ Mathematical optimization
/ Operations research
/ Operations Research/Decision Theory
/ Pricing
/ Programming
/ Propagation
/ Resource allocation
/ Solvers
/ Studies
/ Theory of Computation
/ Variables
2013
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Constraint Programming-based Column Generation
by
Malucelli, Federico
, Gualandi, Stefano
in
Algorithms
/ Business and Management
/ Column packings
/ Combinatorial analysis
/ Combinatorics
/ Decomposition
/ Flexibility
/ Graph coloring
/ Labeling
/ Linear programming
/ Mathematical optimization
/ Operations research
/ Operations Research/Decision Theory
/ Pricing
/ Programming
/ Propagation
/ Resource allocation
/ Solvers
/ Studies
/ Theory of Computation
/ Variables
2013
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Do you wish to request the book?
Constraint Programming-based Column Generation
by
Malucelli, Federico
, Gualandi, Stefano
in
Algorithms
/ Business and Management
/ Column packings
/ Combinatorial analysis
/ Combinatorics
/ Decomposition
/ Flexibility
/ Graph coloring
/ Labeling
/ Linear programming
/ Mathematical optimization
/ Operations research
/ Operations Research/Decision Theory
/ Pricing
/ Programming
/ Propagation
/ Resource allocation
/ Solvers
/ Studies
/ Theory of Computation
/ Variables
2013
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Journal Article
Constraint Programming-based Column Generation
2013
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Overview
This paper surveys recent applications and advances of the Constraint Programming-based Column Generation framework, where the master subproblem is solved by traditional OR techniques, while the pricing subproblem is solved by Constraint Programming. This framework has been introduced to solve crew assignment problems, where complex regulations make the pricing subproblem demanding for traditional techniques, and then it has been applied to other contexts. The main benefits of using Constraint Programming are the expressiveness of its modeling language and the flexibility of its solvers. Recently, the Constraint Programming-based Column Generation framework has been applied to many other problems, ranging from classical combinatorial problems such as graph coloring and two dimensional bin packing, to application oriented problems, such as airline planning and resource allocation in wireless ad-hoc networks.
Publisher
Springer US,Springer,Springer Nature B.V
Subject
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