TY - GEN
T1 - Global multiobjective optimization via estimation of distribution algorithm with biased initialization and crossover
AU - Zhou, Aimin
AU - Zhang, Qingfu
AU - Jin, Yaochu
AU - Sendhoff, Bernhard
AU - Tsang, Edward
PY - 2007
Y1 - 2007
N2 - Multiobjective optimization problems with many local Pareto fronts is a big challenge to evolutionary algorithms. In this paper, two operators, biased initialization and biased crossover, are proposed to improve the global search ability of RM-MEDA, a recently proposed multiobjective estimation of distribution algorithm. Biased initialization inserts several globally Pareto optimal solutions into the initial population; biased crossover combines the location information of some best solutions found so far and globally statistical information extracted from current population. Experiments have been conducted to study the effects of these two operators.
AB - Multiobjective optimization problems with many local Pareto fronts is a big challenge to evolutionary algorithms. In this paper, two operators, biased initialization and biased crossover, are proposed to improve the global search ability of RM-MEDA, a recently proposed multiobjective estimation of distribution algorithm. Biased initialization inserts several globally Pareto optimal solutions into the initial population; biased crossover combines the location information of some best solutions found so far and globally statistical information extracted from current population. Experiments have been conducted to study the effects of these two operators.
KW - Biased
KW - Biased initialization
KW - Estimation of distribution algorithm
KW - Global optimization
KW - Multiobjective optimization
UR - https://www.scopus.com/pages/publications/34548078158
U2 - 10.1145/1276958.1277082
DO - 10.1145/1276958.1277082
M3 - 会议稿件
AN - SCOPUS:34548078158
SN - 1595936971
SN - 9781595936974
T3 - Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference
SP - 617
EP - 623
BT - Proceedings of GECCO 2007
T2 - 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
Y2 - 7 July 2007 through 11 July 2007
ER -