Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Bin Packing with Item Fragmentation
WADS '01 Proceedings of the 7th International Workshop on Algorithms and Data Structures
Using Extra Dual Cuts to Accelerate Column Generation
INFORMS Journal on Computing
Parallelism versus Memory Allocation in Pipelined Router Forwarding Engines
Theory of Computing Systems
Improved Results for a Memory Allocation Problem
Theory of Computing Systems
Approximation schemes for packing with item fragmentation
WAOA'05 Proceedings of the Third international conference on Approximation and Online Algorithms
Branching in branch-and-price: a generic scheme
Mathematical Programming: Series A and B
The Bin Packing Problem with Precedence Constraints
Operations Research
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In this paper we consider a class of bin packing problems from the literature having the following distinctive feature: items may be fragmented at a price. Problems of this kind arise in diverse application fields like logistics and telecommunications, and have already been extensively tackled from an approximation point of view. We focus on the case in which splitting produces no overhead, a fixed number of bins is given and the number of fragments or fragmentations needs to be minimized. We first investigate the theoretical properties of the problem. Then we elaborate on them to devise mathematical programming models and algorithms, yielding both exact optimization algorithms and effective heuristics. An extensive experimental campaign proves that our approach is very effective, and highlights which features make an instance computationally harder to solve.