# Utilising a Quantum Hybrid Solver for Bi-objective Quadratic Assignment Problems

arXiv: https://arxiv.org/abs/2405.17676 · HTML: https://mlsanity.com/paper/2405.17676/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 5 references that are in the map.
- First posted on arXiv 27 May 2024.

## Builds on (most cited first, 4 of 4)

- [pymoo: Multi-objective Optimization in Python](https://mlsanity.com/paper/2002.04504/) (2020)
- [Multi-objective QUBO Solver: Bi-objective Quadratic Assignment](https://mlsanity.com/paper/2205.13399/) (2022)
- [A Study of Scalarisation Techniques for Multi-Objective QUBO Solving](https://mlsanity.com/paper/2210.11321/) (2022)
- [Applying Ising Machines to Multi-objective QUBOs](https://mlsanity.com/paper/2305.11648/) (2023)

## Abstract (arXiv)

The intersection between quantum computing and optimisation has been an area of interest in recent years. There have been numerous studies exploring the application of quantum and quantum-hybrid solvers to various optimisation problems. This work explores scalarisation methods within the context of solving the bi-objective quadratic assignment problem using a quantum-hybrid solver. We show results that are consistent with previous research on a different Ising machine.