DocumentCode :
3338919
Title :
An Improved Multi-objective evolutionary Algorithm for hypertension nutritional diet Problems
Author :
Wang, Gaoping ; Sun, Yanping
Author_Institution :
Coll. of Inf. Sci. & Technol., Henan Univ. of Technol., Zhengzhou, China
Volume :
1
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
312
Lastpage :
315
Abstract :
Unlike traditional single objective method, hypertension design is represented as a multi-objective optimization problem. In this paper, we present an improved multi-objective genetic algorithm to solve hypertension nutritional diet problems. Simulated annealing is presented to overcome deficiencies such as the poor local search and premature convergence of multi-objective genetic algorithm. The experimental results indicate that this algorithm is quite effective for hypertension design and provides powerful decision support to the design-maker.
Keywords :
diseases; genetic algorithms; medical diagnostic computing; simulated annealing; decision support; evolutionary algorithm; genetic algorithm; hypertension nutritional diet problems; simulated annealing; Algorithm design and analysis; Blood pressure; Cardiovascular diseases; Constraint optimization; Decision making; Evolutionary computation; Genetic algorithms; Hypertension; Paper technology; Weight control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-3928-7
Electronic_ISBN :
978-1-4244-3930-0
Type :
conf
DOI :
10.1109/ITIME.2009.5236407
Filename :
5236407
Link To Document :
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