Dynamic programming revisited: improving knapsack algorithms
Computing - Special issue on combinatorial optimization
Linear time algorithms for knapsack problems with bounded weights
Journal of Algorithms
New heuristics for one-dimensional bin-packing
Computers and Operations Research
A stabilized branch-and-price-and-cut algorithm for the multiple length cutting stock problem
Computers and Operations Research
Solving the variable size bin packing problem with discretized formulations
Computers and Operations Research
Heuristics for the one-dimensional cutting stock problem with limited multiple stock lengths
Computers and Operations Research
Heuristics for the variable sized bin-packing problem
Computers and Operations Research
Modified subset sum heuristics for bin packing
Information Processing Letters
Relaxations and exact solution of the variable sized bin packing problem
Computational Optimization and Applications
Worst-case analysis of the subset sum algorithm for bin packing
Operations Research Letters
Comparing several heuristics for a packing problem
International Journal of Advanced Intelligence Paradigms
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In this paper we present a local search heuristic for real-life instances of the variable size bin packing problem, and an exact algorithm for small instances. One important issue our heuristic is able to satisfy is that solutions must be delivered within (milli)seconds and that the solution methods should be robust to last minute changes in the data. Furthermore we show that we are able to incorporate the concept of usable leftovers on a single bin, and the implementation of many additional constraints should be supported by the straightforward solution representation. The heuristic is compared to others from the literature, and comes out ahead on a large subset of the instances.