二次无约束二元优化问题单翻转局部最优解的约束规划法
Constraint Programming to Discover One-Flip Local Optima of Quadratic Unconstrained Binary Optimization Problems
摘要：
二次无约束二进制优化（QUBO）的广泛适用性构成了组合优化问题的通用建模框架，并且是门阵列和量子退火计算机所需的格式。QUBO退火机以及其他解决方案方法受益于从具有局部最优性的一组不同的解决方案开始的额外好处。本文提出了一种利用约束规划生成一组单翻转局部最优解的新方法。此外，如实验测试中所示，对解集的分析允许生成软约束以帮助指导优化过程。
英文摘要：
The broad applicability of Quadratic Unconstrained Binary Optimization (QUBO) constitutes a general-purpose modeling framework for combinatorial optimization problems and are a required format for gate array and quantum annealing computers. QUBO annealers as well as other solution approaches benefit from starting with a diverse set of solutions with local optimality an additional benefit. This paper presents a new method for generating a set of one-flip local optima leveraging constraint programming. Further, as demonstrated in experimental testing, analysis of the solution set allows the generation of soft constraints to help guide the optimization process.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
