CAJ | 학술논문

为了改善差分进化算法的收敛速度和优化精度, 提出一种基于复形法和云模型的差分进化混合算法（HDECC）。该算法使用差分进化算法搜索局部最优域, 引入复形法和云模型来加快算法的收敛速度和提高算法优化精度, 使算法的初期搜索速度和之后的优化精度得到相互平衡。最后, 使用七个标准约束优化问题和两个典型工程应用实例进行实验仿真, 实验结果表明, 与同类算法比较, HDECC算法全局搜索能力强、优化精度高、收敛速度快, 且算法更稳定。
위료개선차분진화산법적수렴속도화우화정도, 제출일충기우복형법화운모형적차분진화혼합산법（HDECC）。해산법사용차분진화산법수색국부최우역, 인입복형법화운모형래가쾌산법적수렴속도화제고산법우화정도, 사산법적초기수색속도화지후적우화정도득도상호평형。최후, 사용칠개표준약속우화문제화량개전형공정응용실례진행실험방진, 실험결과표명, 여동류산법비교, HDECC산법전국수색능력강、우화정도고、수렴속도쾌, 차산법경은정。
In order to improve the differential evolution algorithms convergence speed and optimization accuracy, this paper proposed a new algorithm which named a hybrid differential evolution algorithm based on complex method and cloud model (HDECC). The new algorithm used the differential evolution algorithm to search the optimal area first, then introduced the complex method to accelerate the convergence rate of the algorithm and made use of cloud model to improve the optimization accuracy of the algorithm, so that it balanced the preliminary search speed and accuracy in the later stage. Finally, it used seven standard constrained optimization problems and two typical engineering applications to simulate. Experimental results show that, compared with similar algorithms, HDECC is robust in solving global optimal solution, has higher accurate numerical solution, achieves more rapid convergence rate, and maintains good stability.