Phase transition and landscape statistics of the number partitioning problem
Peter F. Stadler, Wim Hordijk, Jos\'e F. Fontanari

TL;DR
This paper investigates the phase transition in the number partitioning problem by analyzing its energy landscape through barrier trees, revealing that only a specific difficulty measure detects the transition, and comparing the landscape to random trees.
Contribution
It introduces a novel landscape analysis of NPP using barrier trees and identifies a specific difficulty measure that detects the phase transition.
Findings
Barrier trees of NPP resemble random trees.
Difficulty measure detects phase transition traces.
NPP landscape differs from spin-glass models.
Abstract
The phase transition in the number partitioning problem (NPP), i.e., the transition from a region in the space of control parameters in which almost all instances have many solutions to a region in which almost all instances have no solution, is investigated by examining the energy landscape of this classic optimization problem. This is achieved by coding the information about the minimum energy paths connecting pairs of minima into a tree structure, termed a barrier tree, the leaves and internal nodes of which represent, respectively, the minima and the lowest energy saddles connecting those minima. Here we apply several measures of shape (balance and symmetry) as well as of branch lengths (barrier heights) to the barrier trees that result from the landscape of the NPP, aiming at identifying traces of the easy/hard transition. We find that it is not possible to tell the easy regime…
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