TY - GEN
T1 - An improved estimation of distribution algorithm in dynamic environments
AU - Liu, Xiaoxiong
AU - Wu, Yan
AU - Ye, Jimin
PY - 2008
Y1 - 2008
N2 - In dynamic environments, the optimal solution changes over time. To track the solution, an improved univariate marginal distribution algorithm(UMDA) is proposed. A transfer model is introduced to increase the diversity of population. The current information is used to avoid being trapped into the local optimization for dynamic optimization problems. The scheme is illustrated through simulations applying dynamic moving peaks benchmark. The results show that the proposed algorithm is effective and can accommodate the dynamic environments rapidly.
AB - In dynamic environments, the optimal solution changes over time. To track the solution, an improved univariate marginal distribution algorithm(UMDA) is proposed. A transfer model is introduced to increase the diversity of population. The current information is used to avoid being trapped into the local optimization for dynamic optimization problems. The scheme is illustrated through simulations applying dynamic moving peaks benchmark. The results show that the proposed algorithm is effective and can accommodate the dynamic environments rapidly.
UR - http://www.scopus.com/inward/record.url?scp=57649238368&partnerID=8YFLogxK
U2 - 10.1109/ICNC.2008.121
DO - 10.1109/ICNC.2008.121
M3 - 会议稿件
AN - SCOPUS:57649238368
SN - 9780769533049
T3 - Proceedings - 4th International Conference on Natural Computation, ICNC 2008
SP - 269
EP - 272
BT - Proceedings - 4th International Conference on Natural Computation, ICNC 2008
T2 - 4th International Conference on Natural Computation, ICNC 2008
Y2 - 18 October 2008 through 20 October 2008
ER -