计算机系统应用
計算機繫統應用
계산궤계통응용
APPLICATIONS OF THE COMPUTER SYSTEMS
2014年
11期
175-180
,共6页
群搜索优化算法%动态环境%感知者%多发现者%群体多样性
群搜索優化算法%動態環境%感知者%多髮現者%群體多樣性
군수색우화산법%동태배경%감지자%다발현자%군체다양성
group search optimizer%dynamic environment%sensitive individual%multi-producer%population diversity
针对基本群搜索算法(GSO)不能及时适应动态环境变化、容易陷入局部极值的问题，提出一种基于感知者角色和多发现者的动态群搜索算法(SMGSO)。引入“感知者”角色用以检测环境变化，重新初始化一定比例的种群个体以响应环境变化；采用多发现者模式，提出了基于多发现者中心的加入者更新模式，以提高搜索精度；采用基于群体多样性的角色分配策略，确定加入者和游荡者的比例与数量，提高种群多样性。实验结果表明，在解决动态寻优问题时， SMGSO算法表现出更好的性能，能够更准确、更及时地跟踪动态目标。
針對基本群搜索算法(GSO)不能及時適應動態環境變化、容易陷入跼部極值的問題，提齣一種基于感知者角色和多髮現者的動態群搜索算法(SMGSO)。引入“感知者”角色用以檢測環境變化，重新初始化一定比例的種群箇體以響應環境變化；採用多髮現者模式，提齣瞭基于多髮現者中心的加入者更新模式，以提高搜索精度；採用基于群體多樣性的角色分配策略，確定加入者和遊盪者的比例與數量，提高種群多樣性。實驗結果錶明，在解決動態尋優問題時， SMGSO算法錶現齣更好的性能，能夠更準確、更及時地跟蹤動態目標。
침대기본군수색산법(GSO)불능급시괄응동태배경변화、용역함입국부겁치적문제，제출일충기우감지자각색화다발현자적동태군수색산법(SMGSO)。인입“감지자”각색용이검측배경변화，중신초시화일정비례적충군개체이향응배경변화；채용다발현자모식，제출료기우다발현자중심적가입자경신모식，이제고수색정도；채용기우군체다양성적각색분배책략，학정가입자화유탕자적비례여수량，제고충군다양성。실험결과표명，재해결동태심우문제시， SMGSO산법표현출경호적성능，능구경준학、경급시지근종동태목표。
Failing to adapt to dynamic changes and depart fromlocal optima are two disadvantages of basic group search optimizer (GSO) in the dynamic environment. A sensitive individuals and multi-producer based dynamic GSO named SMGSO is proposed in this paper for dynamic optimization problems. Firstly, sensitive individuals are introduced in GSO in addition to producer, scroungers and rangers, which are responsible for detecting the environmental change. If environmental changes are detected, some individuals are initialized to respond to them. Secondly, a new update model of scroungers is proposed based on the center of multi-producer to improve local search ability. At last, arole assignment strategy based on population diversitywhichis beneficial for keep stable diversity is adopted to determine the ratio of scroungers to rangers. Experimental results demonstrate that SMGSO is superior to other heuristic algorithms in dynamic environment, which may not only find the optima as possibleas closely but also trackthe changed optimatimely.
