Quantum Inspired Evolutionary Algorithm (QEA) is a type of evolutionary algorithm based on principles of Quantum Computing (QC).
量子衍生进化算法是基于量子计算原理的一种进化算法。
QEA is more suitable for parallel structure than the conventional evolutionary algorithms because of rapid convergence and good global search capability.
此外，量子进化算法具有收敛快和好的全局搜索特性，因此它比传统的进化算法更适于并行结构的实现。
For avoiding the disadvantage, that QEA has a little stronger randomicity, we imported an optimizing operator which make the QEA better adapt to solving MSA problem.
为避免QEA随机性较强的缺点，引入了一个优化算子，使得QEA更好地应用于求解msa问题。
The algorithm is based on the combination of quantum evolutionary algorithm (QEA) and ant colony system (ACS), a new algorithm, quantum ant colony algorithm (QACA) is proposed.
将量子群进化算法(QEA)与蚁群系统(acs)进行融合，提出一种新的量子蚁群算法(QACA)。
Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid Quantum Evolutionary algorithms (QEA) based on combining QEA with Particle Swarm optimization (PSO).
文章将量子进化算法(QEA)和粒子群算法(PSO)互相结合，提出了两种混合量子进化算法。
Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid Quantum Evolutionary algorithms (QEA) based on combining QEA with Particle Swarm optimization (PSO).
文章将量子进化算法(QEA)和粒子群算法(PSO)互相结合，提出了两种混合量子进化算法。
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