将蛛群优化方法(SSO)这一新型群体智能寻优方法引入梯级水库群优化调度领域,并提出精英集聚蛛群优化方法(ESSO)进一步改善SSO的性能表现。ESSO在标准SSO方法寻优机制基础上,从精英个体动态更新策略与邻域变异搜索机制等两方面予以改进,提升蜘蛛群体的多样性与优秀个体领导能力,均衡方法的全局开采能力与局部勘探能力。澜沧江流域工程实例表明,所提ESSO方法能有效克服标准SSO的“早熟”缺陷,有效提升方法的搜索能力,可望为大规模梯级水库群优化调度提供一种新的高效求解思路。 This new group intelligent optimization method based on the spline optimization method (SSO) is introduced into the field of optimal scheduling of cascaded reservoirs, and an elitist clustering optimization method (ESSO) is proposed to further improve the performance of SSO. On the basis of the standard SSO method, ESSO improves on the strategy of individual elite dynamic update and neighborhood mutation search mechanism to enhance the spider population diversity and outstanding individual leadership ability. Equilibrium method’s global mining capability and local exploration ability. The project of Lancang River Basin shows that the proposed ESSO method can effectively overcome the “premature” defect of standard SSO and effectively improve the search capability of the method, which is expected to provide a new and efficient solution for large scale cascade reservoir optimization.