Lower bounds and reduction procedures for the bin packing problem
Discrete Applied Mathematics - Combinatorial Optimization
Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
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
A New Exact Algorithm for General Orthogonal D-Dimensional Knapsack Problems
ESA '97 Proceedings of the 5th Annual European Symposium on Algorithms
An efficient approximation scheme for the one-dimensional bin-packing problem
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Bin packing with items uniformly distributed over intervals [a,b]
SFCS '83 Proceedings of the 24th Annual Symposium on Foundations of Computer Science
Higher-Dimensional Packing with Order Constraints
WADS '01 Proceedings of the 7th International Workshop on Algorithms and Data Structures
An Exact Algorithm for the Two-Dimensional Strip-Packing Problem
Operations Research
Computers and Operations Research
Conservative scales in packing problems
OR Spectrum
Improved bounds for hybrid flow shop scheduling with multiprocessor tasks
Computers and Industrial Engineering
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The bin packing problem is one of the classical NP-hard optimization problems. Even though there are many excellent theoretical results, including polynomial approximation schemes, there is still a lack of methods that are able to solve practical instances optimally. In this paper, we present a fast and simple generic approach for obtaining new lower bounds, based on dual feasible functions. Worst case analysis as well as computational results show that one of our classes clearly outperforms the currently best known "economical" lower bound for the bin packing problem by Martello and Toth, which can be understood as a special case. This indicates the usefulness of our results in a branch and bound framework.