Cached Iterative Weakening for Optimal Multi-Way Number Partitioning
Abstract
The NP-hard number-partitioning problem is to separate a multiset S of n positive integers into k subsets, such that the largest sum of the integers assigned to any subset is minimized. The classic application is scheduling a set of n jobs with different run times onto k identical machines such that the makespan, the time to complete the schedule, is minimized. We present a new algorithm, cached iterative weakening (CIW), for solving this problem optimally. It incorporates three ideas distinct from the previous state of the art: it explores the search space using iterative weakening instead of branch and bound; generates feasible subsets once and caches them instead of at each node of the search tree; and explores subsets in cardinality order instead of an arbitrary order. The previous state of the art is represented by three different algorithms depending on the values of n and k. We provide one algorithm which outperforms all previous algorithms for k >= 4. Our run times are up to two orders of magnitude faster.
Cite
Text
Schreiber and Korf. "Cached Iterative Weakening for Optimal Multi-Way Number Partitioning." AAAI Conference on Artificial Intelligence, 2014. doi:10.1609/AAAI.V28I1.9122Markdown
[Schreiber and Korf. "Cached Iterative Weakening for Optimal Multi-Way Number Partitioning." AAAI Conference on Artificial Intelligence, 2014.](https://mlanthology.org/aaai/2014/schreiber2014aaai-cached/) doi:10.1609/AAAI.V28I1.9122BibTeX
@inproceedings{schreiber2014aaai-cached,
title = {{Cached Iterative Weakening for Optimal Multi-Way Number Partitioning}},
author = {Schreiber, Ethan L. and Korf, Richard E.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2014},
pages = {2738-2745},
doi = {10.1609/AAAI.V28I1.9122},
url = {https://mlanthology.org/aaai/2014/schreiber2014aaai-cached/}
}