计算机工程
計算機工程
계산궤공정
COMPUTER ENGINEERING
2009年
15期
10-12
,共3页
亲缘选择%遗传算法%早熟收敛
親緣選擇%遺傳算法%早熟收斂
친연선택%유전산법%조숙수렴
kin selection%Genetic Algorithm(GA)%premature convergence
针对传统遗传算法容易陷入局部最优解的缺陷,借鉴生物中亲缘选择的思想,提出基于亲缘选择的遗传算法.该算法构造新选择算子,通过按亲缘关系放弃一个解而获得另一个解来保证算法在最优解的领域内的有效搜索,提高遗传算法对全局最优解的搜索能力和收敛速度.仿真结果表明,该算法正确有效,性能优于现有的传统算法.
針對傳統遺傳算法容易陷入跼部最優解的缺陷,藉鑒生物中親緣選擇的思想,提齣基于親緣選擇的遺傳算法.該算法構造新選擇算子,通過按親緣關繫放棄一箇解而穫得另一箇解來保證算法在最優解的領域內的有效搜索,提高遺傳算法對全跼最優解的搜索能力和收斂速度.倣真結果錶明,該算法正確有效,性能優于現有的傳統算法.
침대전통유전산법용역함입국부최우해적결함,차감생물중친연선택적사상,제출기우친연선택적유전산법.해산법구조신선택산자,통과안친연관계방기일개해이획득령일개해래보증산법재최우해적영역내적유효수색,제고유전산법대전국최우해적수색능력화수렴속도.방진결과표명,해산법정학유효,성능우우현유적전통산법.
An improved Genetic Algorithm(GA) based on the kin selection in biology is proposed to avoid the problem of local optimum. The key to this algorithm lies in the construction of a new selection operator, which offers a solution by sacrificing a solution for its kin. By doing so, it ensures an efficiently guided, through search in the neighhnurhood of the best solution. This algorithm improves the ability of searching an optimum solution and increases the convergence speed. It has extensive applications for many practical optimization problems. Simulation result proves its effectiveness and better performance.