Genetic algorithm with local optimization

A hybrid multi-objective optimization algorithm based on genetic algorithm and stochastic local search is developed and evaluated. The single agent stochastic search local optimization algorithm has been modified in order to be suitable for multi-objective optimization where the local optimization is performed towards non-dominated points. The presented algorithm has been experimentally investigated by solving a set of well known test problems, and evaluated according to several metrics for measuring the performance of algorithms for multi-objective optimization. Results of the experimental investigation are presented and discussed.

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Application of Multidirectional Mutation Genetic Algorithm and Its Optimization Neural Network in Intelligent Optimization of English Teaching Courses

Computational Intelligence and Neuroscience ◽

10.1155/2021/4297600 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Zi Yang

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Bp Neural Network ◽

Optimization Problems ◽

Local Optimization ◽

Bp Algorithm ◽

Control Group ◽

Intelligent Optimization ◽

English Teaching ◽

Optimization System

Aiming at the problems existing in the traditional teaching mode, this paper intelligently optimizes English teaching courses by using multidirectional mutation genetic algorithm and its optimization neural network method. Firstly, this paper gives the framework of intelligent English course optimization system based on multidirectional mutation genetic BP neural network and analyses the local optimization problems existing in the traditional BP algorithm. A BP neural network optimization algorithm based on multidirectional mutation genetic algorithm (MMGA-BP) is presented. Then, the multidirectional mutation genetic BPNN algorithm is applied to the intelligent optimization of English teaching courses. The simulation shows that the multidirectional mutation genetic BP neural network algorithm can solve the local optimization problem of traditional BP neural network. Finally, a control group and an experimental group are set up to verify the role of multidirectional mutation genetic algorithm and its optimization neural network in the intelligent optimization system of English teaching courses through the combination of summative and formative teaching evaluations. The data show that MMGA-BP algorithm can significantly improve the scores of academic students in English courses and has better teaching performance. The effect of vocabulary teaching under the guidance of MMGA-BP optimization theory is very significant, which plays a certain role in the intelligent curriculum optimization of the experimental class.

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A Hybrid Algorithm by Combination of Genetic Algorithm and Local Optimization for Constrained MHD Pump Optimization

2018 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM) ◽

10.1109/cistem.2018.8613589 ◽

2018 ◽

Cited By ~ 1

Author(s):

Khadidja Bouali ◽

Fatima Zohra Kadid ◽

Rachid Abdessemed

Keyword(s):

Genetic Algorithm ◽

Hybrid Algorithm ◽

Local Optimization

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