A Tight (3/2 + ∈ )-Approximation Algorithm for Demand Strip Packing
Franziska Eberle, Felix Hommelsheim, Malin Rau, Stefan Walzer
Abstract
We consider the Demand Strip Packing problem (DSP), in which we are given a set of jobs, each specified by a processing time and a demand. The task is to schedule all jobs such that they are finished before some deadline D while minimizing the peak demand, i.e., the maximum total demand of tasks executed at any point in time. DSP is closely related to the Strip Packing problem (SP), in which we are given a set of axis-aligned rectangles that must be packed into a strip of fixed width while minimizing the maximum height. DSP and SP are known to be NP-hard to approximate to within a factor below
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 8e7c6072-3800-4890-bab4-7552cbfd895fRelated papers
- Augmenting Packing Dynamic Programs to Handle (Many) Additional Budget ConstraintsAlexander Armbruster, Fabrizio Grandoni, Antoine Tinguely, Andreas WieseSODA 2026 · 2 citations
- On Minimizing Tardy Processing Time, Max-Min Skewed Convolution, and Triangular Structured ILPsKim-Manuel Klein, Adam Polak, Lars RohwedderSODA 2023 · 5 citations
- Improved Approximation Algorithms for Non-preemptive Throughput MaximizationAlexander Armbruster, Fabrizio Grandoni, Antoine Tinguely, Andreas WieseSTOC 2026 · 1 citation
- Tight (S)ETH-Based Lower Bounds for Pseudopolynomial Algorithms for Bin Packing and Multi-machine SchedulingKarl Bringmann, Anita Dürr, Karol WegrzyckiSTOC 2026 · 6 citations
- Almost Optimal Inapproximability of Multidimensional Packing ProblemsSai SandeepFOCS 2021 · 9 citations
