CAJ | 학술논문

针对非线性多峰函数的优化问题求解困难，提出一种双种群进化策略快速收敛的算法。首先，对于该类最优化问题使用双种群随机变量作为变异算子，在两个不同的子群间并行进行进化，通过使用不同的突变算子策略，实现种群在求解空间具有尽可能分散地搜索的同时在局部也具有尽可能细致的搜索能力。通过子群重组实现子群问的信息交换，通过仿真实例可看出，该算法在非线性多峰值函数优化问题中，具有求解精度较高，收敛速度较快等特点。
침대비선성다봉함수적우화문제구해곤난，제출일충쌍충군진화책략쾌속수렴적산법。수선，대우해류최우화문제사용쌍충군수궤변량작위변이산자，재량개불동적자군간병행진행진화，통과사용불동적돌변산자책략，실현충군재구해공간구유진가능분산지수색적동시재국부야구유진가능세치적수색능력。통과자군중조실현자군문적신식교환，통과방진실례가간출，해산법재비선성다봉치함수우화문제중，구유구해정도교고，수렴속도교쾌등특점。
For solving the problem of nonlinear muhimodal function optimization, this paper presents a bi - group evolutionary strategies as a fast convergent algorithm. First of all, for this kind of optimization problems, we use bi - group random variables as the mutation operator and the algorithm of evolution in two different subgroups are parallel performed by using different mutation strategic8 to make the group in the solution space to he deeentralizedly explorated as possible while in the local to be carefully done. The exchange of information between supgroups is realized by reorganizing them. We, through the examples, can see that the algorithm in solving the problem of the nonlinear multimodal function optimization has the features like high precision, fast convergence rate etc.