量子进化算法研究进展  

Advances in quantum-inspired evolutionary algorithms

作　　者：王凌[1,2] 

机构地区：[1]清华信息科学与技术国家实验室,北京100084 [2]清华大学自动化系,北京100084

出　　处：《控制与决策》2008年第12期1321-1326,共6页Control and Decision

基　　金：国家自然科学基金项目(60774082);国家863计划项目(2007AA04Z155);国家973计划项目(2002CB312200)

摘　　要：在介绍量子进化算法(QEA)的原理、特点和基本流程的基础上,重点综述QEA的改进,包括改进基本算子、引入新算子、改变种群规模、扩展为并行算法和构造新型算法框架等.介绍了QEA的应用研究,进而提出了QEA在理论、算法、组合优化、多目标优化与约束优化、不确定优化及应用方面的若干进一步的研究内容.After introducing the mechanism, features and basic procedure of quantum-inspired evolutionary algorithm （QEA）, the improvements on QEA are surveyed in detail, including improving the basic operators, introducing novel operators, varying population size, extending to parallel algorithms, constructing novel algorithmetic framework, and so on. Moreover, the applications of QEA are surveyed as well. Furthermore, some future research contents with respect to theory, algorithms, combinational optimization, multi-objective optimization, constrained optimization, stochastic optimization and applications are pointed out.

关 键 词：量子进化算法 量子位 量子计算 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]