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Hybrid Quantum Annealing Heuristic Method for Solving Job Shop Scheduling Problem

机译：解决车间作业调度问题的混合量子退火启发式方法

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Scheduling problems have attracted the attention of researchers and practitioners for several decades. The quality of different methods developed to solve these problems on classical computers have been collected and compared in various benchmark repositories. Recently, quantum annealing has appeared as promising approach to solve some scheduling problems. The goal of this paper is to check experimentally if and how this approach can be applied for solving a well-known benchmark of the classical Job Shop Scheduling Problem. We present the existing capabilities provided by the D-Wave 2000Q quantum annealing system in the light of this benchmark. We have tested the quantum annealing system features experimentally, and proposed a new heuristic method as a proof-of-concept. In our approach we decompose the considered scheduling problem into a set of smaller optimization problems which fit better into a limited quantum hardware capacity. We have tuned experimentally various parameters of limited fully-connected graphs of qubits available in the quantum annealing system for the heuristic. We also indicate how new improvements in the upcoming D-Wave quantum processor might potentially impact the performance of our approach.
机译：调度问题已引起研究人员和从业人员的关注，已有数十年的历史了。在各种基准存储库中已收集并比较了解决经典计算机上解决这些问题的各种方法的质量。最近，量子退火已成为解决某些调度问题的有前途的方法。本文的目的是通过实验检查这种方法是否以及如何应用于解决经典Job Shop Scheduling问题的众所周知的基准。根据此基准，我们介绍了D-Wave 2000Q量子退火系统提供的现有功能。我们已经通过实验测试了量子退火系统的功能，并提出了一种新的启发式方法作为概念验证。在我们的方法中，我们将考虑的调度问题分解为一组较小的优化问题，这些问题更适合于有限的量子硬件容量。我们已经对量子退火系统中可用的量子位的有限完全连接图的实验参数进行了调整，以进行启发式分析。我们还指出了即将到来的D-Wave量子处理器的新改进可能如何影响我们方法的性能。

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