,
Felix Ohnesorge
,
Lis Pirotton
Creative Commons Attribution 4.0 International license
Consider a high-multiplicity Bin Packing instance I with d distinct item types. In 2014, Goemans and Rothvoss gave an algorithm with runtime (|I|²)^O(d) for this problem [SODA'14], where |I| denotes the encoding length of the instance I. Although Jansen and Klein [SODA'17] later developed an algorithm that improves upon this runtime in a special case, it has remained a major open problem by Goemans and Rothvoss [J.ACM'20] whether the doubly exponential dependency on d is necessary. We solve this open problem by showing that unless the Exponential Time Hypothesis (ETH) fails, there is no algorithm solving the high-multiplicity Bin Packing problem in time (|I|²)^o(d). To prove this, we introduce a novel reduction from 3-SAT. The core of our construction is efficiently encoding all information from a 3-SAT instance with n variables into an ILP with O(log n) variables and constraints. This result confirms that the Goemans and Rothvoss algorithm is essentially best-possible for Bin Packing parameterized by the number d of item sizes in the context of XP time algorithms.
@InProceedings{jansen_et_al:LIPIcs.ICALP.2026.116,
author = {Jansen, Klaus and Ohnesorge, Felix and Pirotton, Lis},
title = {{A Tight Double-Exponential Lower Bound for High-Multiplicity Bin Packing}},
booktitle = {53rd International Colloquium on Automata, Languages, and Programming (ICALP 2026)},
pages = {116:1--116:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-428-4},
ISSN = {1868-8969},
year = {2026},
volume = {374},
editor = {Bhattacharya, Sayan and Nanongkai, Danupon and Benedikt, Michael and Puppis, Gabriele},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2026.116},
URN = {urn:nbn:de:0030-drops-265051},
doi = {10.4230/LIPIcs.ICALP.2026.116},
annote = {Keywords: Bin Packing, Lower Bound, Computational Complexity, ETH}
}