太原科技大学学报
太原科技大學學報
태원과기대학학보
JOURNAL OF TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
2014年
3期
180-183,184
,共5页
微粒群算法%最优觅食理论%几何速度稳定性
微粒群算法%最優覓食理論%幾何速度穩定性
미립군산법%최우멱식이론%궤하속도은정성
pArticle swArm optimizAtion(PSo)%optimAl forAging theory%geometric speed stAbility
最优觅食微粒群算法是一种高效的改进微粒群算法，该算法通过引入动物的最优觅食策略，较为真实地模拟了动物的觅食行为。利用几何速度稳定性分析了最优觅食微粒群算法的稳定性，给出了稳定性条件。为验证其性能，选取了5个典型测试函数，仿真结果证明了该策略的有效性。
最優覓食微粒群算法是一種高效的改進微粒群算法，該算法通過引入動物的最優覓食策略，較為真實地模擬瞭動物的覓食行為。利用幾何速度穩定性分析瞭最優覓食微粒群算法的穩定性，給齣瞭穩定性條件。為驗證其性能，選取瞭5箇典型測試函數，倣真結果證明瞭該策略的有效性。
최우멱식미립군산법시일충고효적개진미립군산법，해산법통과인입동물적최우멱식책략，교위진실지모의료동물적멱식행위。이용궤하속도은정성분석료최우멱식미립군산법적은정성，급출료은정성조건。위험증기성능，선취료5개전형측시함수，방진결과증명료해책략적유효성。
optimAl forAging pArticle swArm optimizAtion Algorithm(oFPSo)is A vAriAnt version of pArticle swArm optimizAtion by incorporAting the optimAl forAging theory,the Algorithm introduced the optimAl forAging strAtegies of AnimAlsAnd more reAlisticAlly simulAted the forAging behAvior of AnimAls. In this pAper,the stAbility condition for oFPSo wAs discussed by Applying the geometric speed stAbility. Five typicAl test functions were selected to test the performAnce. SimulAtion results show thAt such Algorithm is effective.
