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中文摘要：
基于量子进化算法和竞争决策算法及进化博弈论,提出一种新型优化算法——量子竞争决策算法。将量子个体作为博弈者参与到优化中,通过竞争力函数和决策函数及量子门更新,实现博弈者自学习和自优化的目的,利用叠加态等特性,提高竞争群体的多样性。通过对典型复杂函数的实验和与其他算法的比较,结果表明算法能有效避免局部最优,全局优化能力强。
英文摘要：
This paper proposes a novel optimization algorithm-quantum competitive decision algorithm,which is based on competitive decision algorithm,evolutionary game theory and quantum evolutionary algorithm.The quantum individuals as game players are introduced into optimization.The algorithm makes competitors possess the abilities of self-learning and self-evolution by competitive force function,decision function and quantum gate updating.The population diversity is increased by superposition characteristic and other characteristics.The results of experiments on typical complex function optimization and comparison with other algorithms show that the algorithm can avoid local optimization and has a stronger global optimization capability.
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