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最近两年比较流行的量子进化算法（QEA），能够求解一般的优化问题。算例是一个典型的背包问题（离散二值问题）。-The more popular the last two years the quantum evolutionary algorithm (QEA), be able to solve the general optimization problems. An example is a typical knapsack problem (discrete binary problem
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最近两年流行的量子进化算法程序，能够优化一下基本的问题，本程序是基于一个连续的极值问题。-The last two years the popular quantum-inspired evolutionary algorithm process, to optimize the basic questions about this program is based on a continuous extremal problem.
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量子进化算法和免疫算法都是解决优化问题的强有力算法。在分析了量子进化算法搜索的特点和免疫算法的机理基础上，对它们进行比较，阐明了二者的不同特点-Quantum-inspired evolutionary algorithms and immune algorithms are a powerful algorithm to solve optimization problems. After analyzing the characteristics of the quantum evoluti
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分析量子进化算法和免疫算子的特点,提出一种分级变异的量子进化算法,用于求解多目标优化问题-Analysis of quantum-inspired evolutionary algorithms and immune operator characteristics, presents a hierarchical variation of the quantum-inspired evolutionary algorithm for solving multi-objective optimi
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本文将以改进后的单细胞FPTA2作为硬件演化平台，引入QEA控制其演化过程，通过实验证明在该平台上，QEA对演化过程的控制效果要优于传统的遗传算法。-This paper proposes the use of quantum-inspired evolutionary algorithm in analog evolvable hardware (EHW). The circuit coding representation, chromosome fitness evaluation met
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Quantum-Inspired Evolutionary Algorithm
Approach for Unit Commitment
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