Theory of linear and integer programming
Theory of linear and integer programming
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Minkowski's convex body theorem and integer programming
Mathematics of Operations Research
Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
A Polynomial Algorithm for Multiprocessor Scheduling with Two Job Lengths
Mathematics of Operations Research
On the complexity of computing determinants
Computational Complexity
An asymptotically exact algorithm for the high-multiplicity bin packing problem
Mathematical Programming: Series A and B
An efficient approximation scheme for the one-dimensional bin-packing problem
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Carathéodory bounds for integer cones
Operations Research Letters
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In the cutting stock problem, we are given a set of objects of different types, and the goal is to pack them all in the minimum possible number of identical bins. All objects have integer lengths, and objects of different types have different sizes. The total length of the objects packed in a bin cannot exceed the capacity of the bin. In this paper, we consider the version of the problem in which the number of different object types is constant, and we present a polynomial-time algorithm that computes a solution using at most one more bin than an optimum solution.