D-Wave推出新型混合求解器，提升组合优化问题求解效率。
D-Wave's Nonlinear-Program Hybrid Solver: Description and Performance Analysis
- 结合量子与经典计算的混合算法框架
- 在45个实例上验证三类优化问题性能提升
- 适合需要快速求解组合优化的工业用户
先进量子-经典算法是当前量子计算的核心策略之一。近年来涌现大量混合求解器，多数针对特定应用场景设计。然而，仍有若干成熟方法被广泛用于优化问题求解。在此背景下，D-Wave于2020年推出混合求解器服务，提供一系列旨在加速用户解决时间的算法方案。近期，该服务新增一种非线性规划混合求解器。本文详细描述该求解器，并通过涵盖3个组合优化问题（旅行商问题、背包问题、最大割问题）共45个实例的基准测试评估其性能。为帮助用户更好地使用这一较新的求解器，本文还提供了应用于上述三类问题的具体实现细节。
原文摘要 · Abstract (English)
The development of advanced quantum-classical algorithms is among the most prominent strategies in quantum computing. Numerous hybrid solvers have been introduced recently. Many of these methods are created ad hoc to address specific use cases. However, several well-established schemes are frequently utilized to address optimization problems. In this context, D-Wave launched the Hybrid Solver Service in 2020, offering a portfolio of methods designed to accelerate time-to-solution for users aiming to optimize performance and operational processes. Recently, a new technique has been added to this portfolio: the Nonlinear-Program Hybrid Solver. This paper describes this solver and evaluates its performance through a benchmark of 45 instances across three combinatorial optimization problems: the Traveling Salesman Problem, the Knapsack Problem, and the Maximum Cut Problem. To facilitate the use of this relatively unexplored solver, we provide details of the implementation used to solve these three optimization problems.
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