目标搜索二次无约束二元优化
Goal Seeking Quadratic Unconstrained Binary Optimization
摘要：
二次无约束二进制优化（QUBO）建模和求解框架是量子和数字退火机的要求。然而，任何实际规模的QUBO问题的最优性是非常难以实现的。为了结合特定问题的见解，满足可接受的目标度量或目标的一组不同的解决方案是高层决策的首选。在本文中，我们提出了两种替代方案的目标寻求QUBO最小化偏离给定的目标，以及一个目标周围的值的范围。实验结果表明，该方法的有效性约束编程快速找到一个令人满意的解决方案。
英文摘要：
The Quadratic Unconstrained Binary Optimization (QUBO) modeling and solution framework is a requirement for quantum and digital annealers. However optimality for QUBO problems of any practical size is extremely difficult to achieve. In order to incorporate the problem-specific insights, a diverse set of solutions meeting an acceptable target metric or goal is the preference in high level decision making. In this paper, we present two alternatives for goal-seeking QUBO for minimizing the deviation from a given target as well as a range of values around a target. Experimental results illustrate the efficacy of the proposed approach over Constraint Programming for quickly finding a satisficing set of solutions.
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。
