Journal of Parallel and Distributed Computing
A Strip-Packing Algorithm with Absolute Performance Bound 2
SIAM Journal on Computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Approximate Max-Min Resource Sharing for Structured Concave Optimization
SIAM Journal on Optimization
Packing 2-Dimensional Bins in Harmony
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Approximating the Advertisement Placement Problem
Proceedings of the 9th International IPCO Conference on Integer Programming and Combinatorial Optimization
Reverse-Fit: A 2-Optimal Algorithm for Packing Rectangles
ESA '94 Proceedings of the Second Annual European Symposium on Algorithms
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Approximation schemes for multidimensional packing
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
New approximability and inapproximability results for 2-dimensional Bin Packing
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
On rectangle packing: maximizing benefits
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms for orthogonal packing problems for hypercubes
Theoretical Computer Science
A Structural Lemma in 2-Dimensional Packing, and Its Implications on Approximability
ISAAC '09 Proceedings of the 20th International Symposium on Algorithms and Computation
Rectangle packing with one-dimensional resource augmentation
Discrete Optimization
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We address the problem of packing of a set of n weighted rectangles into a single rectangle so that the total weight of the packed rectangles is maximized. We consider the case of large resources, that is, the single rectangle is ${\it \Omega}(1/\varepsilon^{3})$ times larger than any rectangle to be packed, for small ε0. We present an algorithm which finds a packing of a subset of rectangles with the total weight at least (1−ε) times the optimum. The running time of the algorithm is polynomial in n and 1/ε. As an application we present a (2+ε)-approximation algorithm for a special case of the advertisement placement problem.