Nutritional Diet Decision Using Multi-objective Difference Evolutionary Algorithm

Author

Pei, Zhenkui ; Liu, Zhen

Author_Institution

Coll. of Comput. & Commun. Eng., China Univ. of Pet., Dongying, China

Volume

1

fYear

2009

fDate

6-7 June 2009

Firstpage

77

Lastpage

80

Abstract

The nutrition diet decision problems on Multi-objective optimization are solved by using Compromise Difference Evolutionary (DE) algorithm. This method is equipped with a domination selection operator to enhance its performance by favoring non-dominated individuals in the populations. DE is a population based search algorithm, which is an improved version of Genetic Algorithm (GA). Simulations carried out involved solving nutrition decision using a method that relationships of dominant to determine the fitness, and finding Pareto optimum set for the nutrition decision problem. Compromise Difference Evolutionary found to be stable and more accurate in optimization compared to simple GA.

Keywords

Pareto optimisation; decision making; genetic algorithms; Pareto optimum set; genetic algorithm; multi-objective difference evolutionary algorithm; nutritional diet decision; Computational intelligence; Decision making; Educational institutions; Evolutionary computation; Genetic algorithms; Genetic engineering; Information technology; Pareto optimization; Petroleum; Robustness; Difference Evolutionary; Genetic Algorithm; Pareto; multi-objective optimization; nutrition diet decision;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3645-3

Type

conf

DOI

10.1109/CINC.2009.175

Filename

5231483