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中文摘要：
针对标准入侵杂草算法缺乏信息共享机制的缺陷,将多智能体系统融入标准入侵杂草算法,提出了一种新的多智能体入侵杂草算法。该算法通过多智能体系统中改进的邻域竞争合作算子实现个体间信息的交流,提高收敛速率;利用多智能体系统中的自学习算子增强算法求解精度。五个基准函数测试对比分析结果表明,多智能体入侵杂草算法的求解精度、收敛速度和稳定性优于标准入侵杂草算法、粒子群算法和差分进化算法。
英文摘要：
Concerning absence of information exchange in basic invasive weed optimization,this paper proposed a new multi- agent invasive weed optimization algorithm by introducing muir-agent system. The modified competition ＆ cooperation operator of muh-agent system was to boost the population＇ s communication and elevated the cgnvergence speed. Besides this,it de- signed the self-study operator to improve the solution quality. The comparative experiments have been conducted on five bench- mark test functions, to conclude that the multi-agent invasive weed optimization algorithm outperforms IWO, PSO and DE algo- rithm in convergence quality, speed and stability.
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