A New Optimization Selection for Test Process of Equipment Manufacturing Based on Fused Algorithm

DOI

10.2991/ameii-15.2015.76How to use a DOI?

Keywords

Optimization Selection; Genetic Algorithm; BP Neural Network; Simulated Annealing Algorithm

Abstract

Test optimization selection is a set cover problem, and heuristic algorithm for set covering problem is effective method. A genetic simulated annealing neural network fused algorithm was proposed by fusing the genetic algorithm, BP neural network and the simulated annealing algorithm, the genetic algorithm global search ability, strong ability of BP neural network training algorithm and fast search ability of simulated annealing algorithm were made full use of in this algorithm, the phenomenon falling into local optimum was avoided, and also the search efficiency and accuracy wad improved, the algorithm is applied to solve the test optimization selection problem. Example proves that this algorithm can effectively and quickly obtain test the optimal solution of optimization problems.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Gang Liu
AU  - Fang Li
PY  - 2015/04
DA  - 2015/04
TI  - A New Optimization Selection for Test Process of Equipment Manufacturing Based on Fused Algorithm
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 402
EP  - 405
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.76
DO  - 10.2991/ameii-15.2015.76
ID  - Liu2015/04
ER  -