In more recent years, there has been increasing research interest in exploiting the use of application specific hardware for solving optimisation problems. Examples of solvers that use specialised hardware are IBM's Quantum System One and D-wave's Quantum Annealer (QA) and Fujitsu's Digital Annealer (DA). These solvers have been developed to optimise problems faster than traditional meta-heuristics implemented on general purpose machines. Previous research has shown that these solvers (can optimise many problems much quicker than exact solvers such as GUROBI and CPLEX. Such conclusions have not been made when comparing hardware solvers with classical evolutionary algorithms. Making a fair comparison between traditional evolutionary algorithms, such as Genetic Algorithm (GA), and the DA (or other similar solvers) is challenging because the later benefits from the use of application specific hardware while evolutionary algorithms are often implemented on general-purpose machines. Moreover, quantum or quantum-inspired solvers are limited to solving problems in a specific format. A common formulation used is Quadratic Unconstrained Binary Optimisation (QUBO). Many optimisation problems are however constrained and have natural representations that are non-binary. Converting such problems to QUBO can lead to more problem difficulty and/or larger search space. The question addressed in this paper is whether quantum or quantum-inspired solvers can optimise QUBO transformations of combinatorial optimisation problems faster than classical evolutionary algorithms applied to the same problems in their natural representations. We show that the DA often present better average objective function values than GA on Travelling Salesman, Quadratic Assignment and Multi-dimensional Knapsack Problem instances.
翻译:近些年来,人们越来越有兴趣研究如何利用应用特定硬件来解决优化问题。使用特殊硬件的解决者的例子有IBM的量子系统一和D波的量子安纳利尔(QA)和Fujitsu的数码安纳利尔(DA)。这些解决方案的开发是为了优化问题,比在一般用途机器上实施的传统超重体力程序要快得多。以前的研究表明,这些解决方案(可以比诸如GUROBI和CPLEX等精确解答器更快地优化许多问题。在将硬件解析器与古典进化算法比较时,并没有得出这样的结论。在传统进化算法(GA)和Fujitsu的数码安纳利器(DAnnanaler)之间进行公平的比较,因为这些应用特定硬件的好处较晚,而进化算法则通常在一般用途机器上实施。量或量级解解解的解解解解解解解的解方法仅限于特定格式中解决问题。通用的配方程式是QUdrival 和Oalalalalalalalalation的解析的解答器通常比O化更难。在Oli化过程中更难。 。在不易的读化、更难 和自动解的解的硬化方面,在不易化的解的解的解的解解解解解析化的多的多的多的硬化的多的硬化, 。 。在O化的硬化的多的解的多的硬化是,在不为不制的硬化的硬化的硬化的硬化的硬化、制的硬化的硬化的硬化的硬化,在不制的硬化的硬化的硬化的硬化、制是的硬化的硬化的硬化的硬化的硬化的硬化,在不制是的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化,在不制是不制,在不制的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的硬化的