基于硬约束热启动的量子投资组合优化算法  

A quantum portfolio optimization algorithm based on hard constraint and warm starting

作　　者：蔚栋敏 陈柄任 陈慧 吴磊 李晓瑜 YU Dongmin;CHEN Bingren;CHEN Hui;WU Lei;LI Xiaoyu(CCB Fintech Co.,Ltd.,Shanghai 200120,China;Sichuan Yuanjiang Technology Co.,Ltd.,Chengdu 611730,China;School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China)

机构地区：[1]建信金融科技有限责任公司,上海200120 [2]四川元匠科技有限公司,成都611730 [3]电子科技大学信息与软件工程学院,成都610054

出　　处：《电子科技大学学报》2025年第1期116-124,共9页Journal of University of Electronic Science and Technology of China

基　　金：建信金融科技有限责任公司研究性课题(PO3522083675,PO3523070947,PO3522083587);成都市重点研发支撑计划重大科技应用示范项目(2021-YF09-00114-GX)。

摘　　要：针对金融领域的投资组合优化问题中普遍存在的整数约束难题,提出了一种基于量子近似优化算法的新解法。该算法通过将经典算法得到的连续解编码为量子电路的初始态,从而将连续优化问题转化为离散的马科维茨模型。同时,引入硬约束来严格满足投资组合中的整数约束,确保解的质量。通过热启动技术,进一步提升了算法的成功率。数值模拟实验表明,该算法在求解大规模整数约束投资组合问题时,相较于传统方法具有显著的计算效率优势,且所得解的质量更优。This paper presents a novel quantum approximate optimization algorithm to address the pervasive integer constraint problem in portfolio optimization within the financial domain.By encoding the continuous solution obtained from classical algorithms into the initial state of a quantum circuit,the algorithm transforms the continuous optimization problem into a discrete Markowitz model.Additionally,hard constraints are introduced to strictly enforce the integer constraints in the portfolio,guaranteeing solution quality.The success rate of the algorithm is further improved by using a warm starting technique.Numerical experiments demonstrate that this algorithm offers significant computational efficiency advantages and a higher solution quality compared to traditional methods when solving large-scale integer-constrained portfolio optimization problems.

关 键 词：量子计算 硬约束 热启动 投资组合优化 量子近似优化算法 

分 类 号：O413.1[理学—理论物理]