Predicting the solutions of a challenging NLP problem with asynchronous parallel evolutionary modeling algorithm

Authors:
Yan Li;Zhen Liu
Affiliations:
State Key Laboratory of Software Engineering, Wuhan University, China;Faculty of Human Environment, Nagasaki Institute of Applied Science, Nagasaki, Japan
Venue:
ISPA'03 Proceedings of the 2003 international conference on Parallel and distributed processing and applications
Year:
2003

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Abstract

In this paper, the asynchronous parallel evolutionary modeling algorithm (APEMA) is used to predict the solutions of a challenging non-linear problem (NLP)-a very high dimensional BUMP problem. Numerical experiments shows that the low order ordinary differential equations (ODE) models give good results.