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A Genetic Algorithm Optimized New Structured Neural Network for Multistage Decision-Making Problem

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4 Author(s)
Lei Yang ; Northeastern University, China ; Yu Dai ; Bin Zhang ; Yan Gao

For the widely use of multistage decision-making problem in our normal life such as in the new research area of dynamic selection of composite web services, this paper exerts all its effort on proposing a new approach to solve such problem. Motivated by neural networks’ high parallel performance and Genetic Algorithm’s powerful computation, a novel Genetic Algorithm optimized neural network is proposed in this paper for this task. In order to make this algorithm more adaptable for multistage decision-making problem, a new neural network structure for implementing the algorithm is proposed which is a modification to the one used by Thomopoulos or Rauch and Winarske.

Published in:

Parallel and Distributed Computing, Applications and Technologies, 2005. PDCAT 2005. Sixth International Conference on

Date of Conference:

05-08 Dec. 2005