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

Eneko Osaba, Esther Villar-Rodriguez, Antón Asla
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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.
在现实世界的仓库优化问题中探索实用性:基于 Quantun 退火炉的表述和初步结果
在当前的 NISQ 时代,研究人员和实践者面临的主要挑战之一是如何以最高效、最创新的方式将量子计算与经典计算结合起来。在本文中,我们提出了一种被称为仓库优化问题量子初始化(Quantum Initialization for Warehouse Optimization Problem)的机制,它采用了 D-Wave 的量子退火器(Quantum Annealer)。该模块经过专门设计,可以嵌入到现有的经典软件中,专门用于优化现实世界中的工业问题。我们通过与经典版本软件的两阶段实验,对实施的机制进行了初步测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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