Approximation algorithms for hitting objects with straight lines
Discrete Applied Mathematics
TCP dynamic acknowledgment delay (extended abstract): theory and practice
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Primal-dual algorithms for deterministic inventory problems
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
A constant approximation algorithm for the one-warehouse multi-retailer problem
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Latency constrained aggregation in sensor networks
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Energy-efficient algorithms for flow time minimization
ACM Transactions on Algorithms (TALG)
Online make-to-order joint replenishment model: primal dual competitive algorithms
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Algorithms for capacitated rectangle stabbing and lot sizing with joint set-up costs
ACM Transactions on Algorithms (TALG)
Improved approximation algorithm for the one-warehouse multi-retailer problem
APPROX'06/RANDOM'06 Proceedings of the 9th international conference on Approximation Algorithms for Combinatorial Optimization Problems, and 10th international conference on Randomization and Computation
A simple and fast 2-approximation algorithm for the one-warehouse multi-retailers problem
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
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The objective of the classical Joint Replenishment Problem (JRP) is to minimize ordering costs by combining orders in two stages, first at some retailers, and then at a warehouse. These orders are needed to satisfy demands that appear over time at the retailers. We investigate the natural special case that each demand has a deadline until when it needs to be satisfied. For this case, we present a randomized 5/3 -approximation algorithm, which significantly improves the best known approximation ratio of 1.8 obtained by Levi and Sviridenko (APPROX'06). We moreover prove that JRP with deadlines is APX-hard, which is the first such inapproximability result for a variant of JRP. Finally, we extend the known hardness results by showing that JRP with linear delay cost functions is NP-hard, even if each retailer has to satisfy only three demands.