CAJ | 학술논문

针对单变量边缘分布算法(UMDA)容易陷入局部最优解且搜索效率较低等缺点,提出一种混合单变量边缘分布算法(HUMDA).该算法采用两阶段参数动态控制策略来控制算法的均值与方差参数,在搜索初期保持群体的多样性,在算法后期提高了算法的局部搜索能力,并引入混沌搜索机制有效提高了算法的搜索精度和效率.采用多峰高维标准测试函数进行测试,测试结果表明 HUMDA 具有更优的全局搜索能力且搜索精度较高.将其应用于求解水库优化调度问题,亦得到较好的结果.
침대단변량변연분포산법(UMDA)용역함입국부최우해차수색효솔교저등결점,제출일충혼합단변량변연분포산법(HUMDA).해산법채용량계단삼수동태공제책략래공제산법적균치여방차삼수,재수색초기보지군체적다양성,재산법후기제고료산법적국부수색능력,병인입혼돈수색궤제유효제고료산법적수색정도화효솔.채용다봉고유표준측시함수진행측시,측시결과표명 HUMDA 구유경우적전국수색능력차수색정도교고.장기응용우구해수고우화조도문제,역득도교호적결과.
In view of the critical shortcomings such as local convergence and low efficiency in univariate marginal distribution algorithm(UMDA), a hybrid univariate marginal distribution algorithm(HUMDA) is proposed. In the proposed method, a two-stage dynamic parameters control strategy is used to control the mean and variance parameters in order to preserve the diversity of population at the beginning of algorithm and improve the local search capability of the algorithm at the end of the execution. In addition, the chaotic search strategy is adopted to enhance the precision of solution and search efficiency. The HUMDA algorithm is tested by the high-dimensional and multimodal functions. The test results show that, the proposed algorithm has better global convergence ability and search accuracy, which is applied to the optimal operation of a reservoir and better results are obtained.