2026-07-22T16:01:33Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:14713 2024-03-06T10:54:43Z ddc:004 open_access

Approximation Algorithms for Demand Strip Packing Gálvez, Waldo Grandoni, Fabrizio Ameli, Afrouz Jabal Khodamoradi, Kamyar Strip Packing Two-Dimensional Packing Approximation Algorithms In the Demand Strip Packing problem (DSP), we are given a time interval and a collection of tasks, each characterized by a processing time and a demand for a given resource (such as electricity, computational power, etc.). A feasible solution consists of a schedule of the tasks within the mentioned time interval. Our goal is to minimize the peak resource consumption, i.e. the maximum total demand of tasks executed at any point in time. It is known that DSP is NP-hard to approximate below a factor 3/2, and standard techniques for related problems imply a (polynomial-time) 2-approximation. Our main result is a (5/3+ε)-approximation algorithm for any constant ε > 0. We also achieve best-possible approximation factors for some relevant special cases. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Waldo Gálvez and Fabrizio Grandoni and Afrouz Jabal Ameli and Kamyar Khodamoradi 2021 Is Part Of LIPIcs, Volume 207, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2021) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.APPROX/RANDOM.2021.20 urn:nbn:de:0030-drops-147130 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2021.20 eng https://creativecommons.org/licenses/by/4.0/legalcode