CAJ | 학술논문

在模拟退火的高斯扰动蝙蝠优化算法（SAGBA ）的基础上，结合解决多目标优化问题的算法技术，探讨了2种改进的多目标蝙蝠算法---基于动态加权的SAGBA 算法（DWASAGBA ）和基于向量估计的SAGBA算法（VESAGBA），并对算法进行了仿真实验。结果表明，SAGBA算法所得到的解集分布均匀，能够得到测试函数较为准确的Pareto曲线。
재모의퇴화적고사우동편복우화산법（SAGBA ）적기출상，결합해결다목표우화문제적산법기술，탐토료2충개진적다목표편복산법---기우동태가권적SAGBA 산법（DWASAGBA ）화기우향량고계적SAGBA산법（VESAGBA），병대산법진행료방진실험。결과표명，SAGBA산법소득도적해집분포균균，능구득도측시함수교위준학적Pareto곡선。
Combined the SAGBA algorithm with the technology of solving the problem of multi-objective optimization ,two kinds of improved multi-objective bat algorithm---the SAGBA algorithm based on dynamic weighted (DWASAGBA) and the SAGBA algorithm based on vector estimation (VESAGBA) are discussed .The simulation experiment results show that the solution set distribution is uniform ,and can get a relatively accurate Pareto curve ,so the SAGBA algorithm is effective in solving multi-objective optimization problems .