计算机科学 ›› 2019, Vol. 46 ›› Issue (2): 315-320.doi: 10.11896/j.issn.1002-137X.2019.02.048
金婷1, 谭文安1,2, 孙勇1, 赵尧1
JIN Ting1, TAN Wen-an1,2, SUN Yong1, ZHAO Yao1
摘要: 目前,基于社会网络的团队形成问题研究大多采取0-1规则度量专家技能。针对人们通常使用自然语言描述专家技能的情况,提出模糊多目标进化的社会团队形成方法。该方法研究模糊环境下如何从专家社会网络中查询出合适的个体并组成规模一定的团队,实现最小的通信代价和最优的团队绩效。其采用模糊语言变量代替以0-1规则为代表的精确参数来描述专家技能,使用团队绩效的概念衡量团队对任务P的技能表现力。鉴于标准SPEA2算法在进化初期收敛速度慢的缺点,引入档案精英学习策略生成优良个体。另外,考虑到专家技能的模糊性,文中提出了细粒度Dominance判断作为判断个体间支配关系的新准则。仿真实验结果证明,改进算法的收敛速度快,获得的近似Pareto前沿更加逼近真实解集,可有效求解团队形成问题。
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