梯级水库群优化调度精英集聚蛛群优化方法

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。

Multi-reservoir operation using elite-gather social spider optimization

The novel meta-heuristic social spider optimization (SSO) provides a new effective way to solve the multi-reservoir optimal operation problem. However, SSO has some disadvantages like premature convergence and poor search ability. Thus,the elite-gather social spider optimization (ESSO) is proposed to alleviate the existing defects of the SSO. ESSO takes advantage of the elite individual to guide the evolution of the population for the globally optimal solution. Moreover, the neighborhood search mechanism is introduced into ESSO to improve the local search ability of the method. The proposed approach is applied to the optimal operation of Lancang River cascade reservoirs, and the results shows that ESSO can improve the convergence property and robustness of SSO. Thus, ESSO is a feasible method for the multi-reservoirs operation problem.