The Application of Genetic Algorithm on Optimization Problem for Mayonnaise Compositions

Abstract:

For some function optimization problems of non-linear, multi-model and multi-objective, they are difficult to solve by other optimization methods, however, genetic algorithm is easy to find good results, so a kind of optimization problem for mayonnaise compositions based on genetic algorithm is introduced. This termination condition is selected according to the iteration number of maximum generation, the optimal solution of last generation in the evolution is the final result with genetic algorithm to solve optimization problem. The population size is 20, crossover rate is 0.7, and mutation rate is 0.04. Via the evolution of 100 generations, the optimization solution is gotten, which has certain guiding significance for the production.

• Periodical: Key Engineering Materials (Volumes 480-481)
• Pages: 219-224
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.480-481.219
• Online since: June 2011
• Authors: Zhi Yang Luo, Hong Xia Zhao, Xin Yuan, Yuan Li
• Keywords: Composition, Function Optimization, Genetic Algorithm (GA), Mayonnaise

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