A population ecology inspired parent selection strategy for numerical constrained optimization problems

Autor:	Jun Hyung Jo, Jong-Hwan Kim, Ming Yuchi
Rok vydání:	2007
Předmět:	education.field_of_study Mathematical optimization Applied Mathematics Numerical analysis Population Selection strategy Constrained optimization Evolutionary algorithm Population ecology Computational Mathematics Constrained optimization problem Penalty method education Mathematics
Zdroj:	Applied Mathematics and Computation. 190:292-304
ISSN:	0096-3003
DOI:	10.1016/j.amc.2007.01.027
Popis:	A population ecology inspired parent selection strategy is proposed to improve the searching ability of evolutionary algorithms for numerical constrained optimization problems. This method is mainly used to help find an appropriate number of feasible parents for offspring generation. Based on the similar phenomenon in population ecology, the number of feasible parents has a sigmoid-type relationship with that of the feasible individuals. To implement the novel parent selection strategy, the population is divided into two groups according to the feasibility of the individuals: the feasible group and infeasible group. The evaluation and ranking of these two groups are performed separately. The dynamic penalty method, annealing penalty method and stochastic ranking method are tested with the parent selection strategy on 13 benchmark problems. The results show that the proposed method is capable of improving the searching performance.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1d4fdce8ea2b9a1d341a9e02a1834283 https://doi.org/10.1016/j.amc.2007.01.027 Zobrazit plný text záznamu Full Text from ScienceDirect