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中文摘要：
针对混沌蚂蚁群优化算法（CASO）容易陷入局部极值和精度低的缺陷，从认知学角度进行分析，将创造性思维（CT）引入CASO算法，提出了一种带创造性思维的混沌蚂蚁群优化算法（CTCASO）。基于CT过程的“四阶段”模型，构建了算法框架，改进了位置更新公式，从而使蚂蚁个体在惯性、认知能力的基础上增强了CT能力，提高了蚁群的整体寻优能力。仿真结果表明，所提出的算法搜索能力强、稳定性好，并且未增加新的参数和计算难度。
英文摘要：
Chaotic ant swarm optimization （CASO） suffers from premature convergence frequently and low accuracy computation. Therefore, the CASO algorithm is analyzed from cognitive science, and a creative thinking （CT） based CASO （CTCASO） algorithm is proposed. Based on the four stages model in CT process, a framework of the CTCASO algorithm is designed, and the evolution model is adapted, which includes a CT model besides the memory model, and the cognitive model in CASO, to improve the optimization capability of ants. The CTCASO algorithm is applied to some well-known benchmarks, and experimental results show that the CTCASO algorithm possesses more powerful search capabilities and robustness, meanwhile it does not introduce new parameters and computational complexity.
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