CAJ | 학술논문

针对经典的微分进化算法难以求解约束优化，特别是大规模复杂约束优化，并且对于多峰值优化无法一次求出多个全局最优解等问题，本文提出了一种改进的微分进化算法。该算法采用一种简单有效的函数对其约束进行处理，并利用全局-局部微分进化算法进行演化。大量测试函数的实验结果表明，这种改进的算法能有效地解决约束优化问题得到全局最优解，并且对于多峰问题能一次得到其多个全局最优解，而且比传统演化算法具有更高的精度和收敛速度。
침대경전적미분진화산법난이구해약속우화，특별시대규모복잡약속우화，병차대우다봉치우화무법일차구출다개전국최우해등문제，본문제출료일충개진적미분진화산법。해산법채용일충간단유효적함수대기약속진행처리，병이용전국-국부미분진화산법진행연화。대량측시함수적실험결과표명，저충개진적산법능유효지해결약속우화문제득도전국최우해，병차대우다봉문제능일차득도기다개전국최우해，이차비전통연화산법구유경고적정도화수렴속도。
In view of the classic differential evolution algorithm is difficult for solving constrained optimization, in particular large-scale, complex constrained optimization, and it can not find the multiple solutions for multi-peak optimization and other issues. The improved differential evolution algorithm is presented in this paper. This algorithm uses a simple and effective function to process its constraints and uses Global-local differential evolutionary algorithm to evolution .A large number of test functions experimental results show that this improved differential evolution algorithm can solve constrained optimization problem effectively and obtain global optimal solution and can obtain multiple solution once for multi-peak problem. It has higher accuracy and convergence rate than traditional methods.