Performance of the Extended Ising Machine for the Quadratic Knapsack Problem

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Akishima, Haruka, Tamura, Hirotaka, Kudo, Kazue
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912532280639488
author Akishima, Haruka
Tamura, Hirotaka
Kudo, Kazue
author_facet Akishima, Haruka
Tamura, Hirotaka
Kudo, Kazue
contents The extended Ising machine (EIM) enhances conventional Ising models, which handle only binary quadratic forms by allowing constraints through real-valued dependent variables. We address the quadratic knapsack problem (QKP), hard to solve using Ising machines when formulated as a quadratic unconstrained binary optimization (QUBO). We demonstrated the EIM's superiority by comparing it with the conventional Ising model-based approach, a commercial exact solver, and a state-of-the-art heuristic solver for QKP.
format Preprint
id arxiv_https___arxiv_org_abs_2508_06909
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Performance of the Extended Ising Machine for the Quadratic Knapsack Problem
Akishima, Haruka
Tamura, Hirotaka
Kudo, Kazue
Statistical Mechanics
Data Structures and Algorithms
The extended Ising machine (EIM) enhances conventional Ising models, which handle only binary quadratic forms by allowing constraints through real-valued dependent variables. We address the quadratic knapsack problem (QKP), hard to solve using Ising machines when formulated as a quadratic unconstrained binary optimization (QUBO). We demonstrated the EIM's superiority by comparing it with the conventional Ising model-based approach, a commercial exact solver, and a state-of-the-art heuristic solver for QKP.
title Performance of the Extended Ising Machine for the Quadratic Knapsack Problem
topic Statistical Mechanics
Data Structures and Algorithms
url https://arxiv.org/abs/2508.06909