Arrow Research search
Back to IJCAI

IJCAI 2009

Conference Paper Constraints, Satisfiability, and Search Artificial Intelligence

Abstract

The number partitioning problem is to divide a given set of integers into a collection of subsets, so that the sum of the numbers in each subset are as nearly equal as possible. While a very efficient algorithm exists for optimal two-way partitioning, it is not nearly as effective for multi-way partitioning. We develop two new linear-space algorithms for multi-way partitioning, and demonstrate their performance on three, four, and five-way partitioning. In each case, our algorithms outperform the previous state of the art by orders of magnitude, in one case by over six orders of magnitude. Empirical analysis of the running times of our algorithms strongly suggest that their asymptotic growth is less than that of previous algorithms. The key insight behind both our new algorithms is that if an optimal k-way partition includes a particular subset, then optimally partitioning the numbers not in that set k−1 ways results in an optimal k-way partition.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
228412085632698806
v2026.09.13