Exploring Utility in a Real-World Warehouse Optimization Problem: Formulation Based on Quantum Annealers and Preliminary Results

TL;DR

This paper introduces a quantum initialization mechanism using D-Wave's Quantum Annealer for warehouse optimization, integrating it with classical software and presenting preliminary experimental results.

Contribution

It proposes a novel hybrid quantum-classical approach for warehouse optimization and demonstrates its integration and initial testing with existing classical systems.

Findings

Preliminary tests show promising results compared to classical methods.

The mechanism can be embedded into existing classical optimization software.

Initial experiments indicate potential advantages of quantum-assisted optimization.

Abstract

In the current NISQ-era, one of the major challenges faced by researchers and practitioners lies in figuring out how to combine quantum and classical computing in the most efficient and innovative way. In this paper, we present a mechanism coined as Quantum Initialization for Warehouse Optimization Problem that resorts to D-Wave's Quantum Annealer. The module has been specifically designed to be embedded into already existing classical software dedicated to the optimization of a real-world industrial problem. We preliminary tested the implemented mechanism through a two-phase experiment against the classical version of the software.