CAJ | 학술논문

为了获取更好的全局寻优性能，同时保持较快的收敛速度，文中结合精英策略、协同进化思想和模拟退火机制，提出了一种基于模拟退火机制的精英协同进化算法( SACEA)。算法维持三个种群：精英种群、普通种群和随机种群。精英个体组团，并和其他组员个体协作或对其引导来达到进化目的。 SACEA算法在精英组团过程中引入随机种群以增加种群多样性，同时随机个体和精英个体的合作采用快速模拟退火机制来实现，使算法获得了更好的全局寻优性。通过对15组标准测试函数的仿真，并和已有的算法进行对比，很容易得出：SACEA算法具有更强的全局寻优能力，同时收敛速度也有所提高。
위료획취경호적전국심우성능，동시보지교쾌적수렴속도，문중결합정영책략、협동진화사상화모의퇴화궤제，제출료일충기우모의퇴화궤제적정영협동진화산법( SACEA)。산법유지삼개충군：정영충군、보통충군화수궤충군。정영개체조단，병화기타조원개체협작혹대기인도래체도진화목적。 SACEA산법재정영조단과정중인입수궤충군이증가충군다양성，동시수궤개체화정영개체적합작채용쾌속모의퇴화궤제래실현，사산법획득료경호적전국심우성。통과대15조표준측시함수적방진，병화이유적산법진행대비，흔용역득출：SACEA산법구유경강적전국심우능력，동시수렴속도야유소제고。
In order to get better global optimization performance and maintain the fast convergence speed,combined with the elite strategy and the concept of co-evolutionary and simulated annealing mechanism,put forward a new algorithm,that is the elite co-evolutionary ge-netic algorithm based on simulated annealing method ( SACEA) . The algorithm maintains three populations including elite population, common population and stochastic population. And then elite individuals form teams and exchange information with other team members with the cooperating operation or leading operation. SACEA introduces the stochastic population to evolution to improve diversity of pop-ulation,at the same time,the stochastic individual and the elite individual using fast simulated annealing method to realize the purpose of cooperation. Through all above,the algorithm gets the better global optimization performance. Simulation on 15 standard test simulation and compared with existing algorithms,it is clearly shown that SACEA has better ability of searching globally optimal solution and makes an improvement in convergence speed.