• 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