欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
提出一种新型优化算法——量子竞争决策算法，在竞争决策的基础上，将进化博弈论中博弈者不断学习和调整来提高竞争力的思想引入到优化中，使竞争者具有自进化能力，同时充分利用量子进化计算中量子比特、叠加态等理论，增加竞争群体的多样性，缩小群体规模。通过对典型的TSP实验计算和与其他算法比较，均取得了较好的效果，算法具有较强的全局优化能力。
英文摘要：
This paper proposed a novel optimization algorithm--quantum competitive decision algorithm. Based on competition and decision, the algorithm introduced the theory of continuous learning and adjustment to improve the competitiveness in evolutionary game theory into optimization, making competitors possess the ability of selfoptimizing. The algorithm made full use of quantum hit, superposition state and other concepts in quantum evolutionary algorithm to increase the diversity of competitors and reduce the population size. Experiments on typical TSP and comparisons with other methods show the new algorithm is more efficient and the algorithm has strong capability of global optimization.
同期刊论文项目
同项目期刊论文
位置：