Lower bounds and reduction procedures for the bin packing problem
Discrete Applied Mathematics - Combinatorial Optimization
Solving binary cutting stock problems by column generation and branch-and-bound
Computational Optimization and Applications
BISON: a fast hybrid procedure for exactly solving the one-dimensional bin packing problem
Computers and Operations Research
Branch-and-Price Algorithms for the One-Dimensional Cutting Stock Problem
Computational Optimization and Applications
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Heuristic Solution of Open Bin Packing Problems
Journal of Heuristics
Optimal Integer Solutions to Industrial Cutting Stock Problems
INFORMS Journal on Computing
A new algorithm for optimal bin packing
Eighteenth national conference on Artificial intelligence
Weighted A∗ search -- unifying view and application
Artificial Intelligence
Bin completion algorithms for multicontainer packing, knapsack, and covering problems
Journal of Artificial Intelligence Research
Bin-completion algorithms for multicontainer packing and covering problems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Solving problems with CP: four common pitfalls to avoid
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
A Branch, Bound, and Remember Algorithm for the Simple Assembly Line Balancing Problem
INFORMS Journal on Computing
Weibull-Based benchmarks for bin packing
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Search strategies for optimal multi-way number partitioning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Improved bin completion for optimal bin packing and number partitioning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Given a set of numbers, and a set of bins of fixed capacity, the NP-complete problem of bin packing is to find the minimum number of bins needed to contain the numbers, such that the sum of the numbers assigned to each bin does not exceed the bin capacity. We present two improvements to our previous bin-completion algorithm. The first speeds up the constant factor per node generation, and the second prunes redundant parts of the search tree. The resulting algorithm appears to be asymptotically faster than our original algorithm. On problems with 90 elements, it runs over 14 times faster. Furthermore, the ratios of node generations and running times both increase with increasing problem size.