LEGUP: using heterogeneity to reduce the cost of data center network upgrades
Proceedings of the 6th International COnference
The train delivery problem: vehicle routing meets bin packing
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Set covering with ordered replacement: additive and multiplicative gaps
IPCO'11 Proceedings of the 15th international conference on Integer programming and combinatoral optimization
The entropy rounding method in approximation algorithms
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Vector bin packing with multiple-choice
Discrete Applied Mathematics
Wireless multicast scheduling with switched beamforming antennas
IEEE/ACM Transactions on Networking (TON)
Computers and Operations Research
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Bin packing is a well-known problem which has a large number of applications. Classical bin packing is a simple model in which all bins are identical. In the bin packing problem with variable-sized bins, we are given a supply of a variety of sizes. This latter model assumes, however, that the cost of a bin is always defined to be its exact size. In this paper we study the more general problem where an available bin size is associated with a fixed cost, which may be smaller or larger than its size. The costs of different bin sizes are unrelated. This generalized problem has various applications in storage and scheduling. In order to generalize previous work, we design new rounding and allocation methods. Our main result is an asymptotic polynomial time approximation scheme for the generalized problem.