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different algorithms to find population close to the optimal fitness, including genetic algorithm, differential evolution algorithm, PSO, firefly algorithm, cuckoo search algorithm and whale optimization algorithm in C++.

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safrannn/optimization

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Optimization

Algorithms to find optimal value for functions

Information

Machine information:

System: MacOS Processor Name: Dual-Core Intel Core i7 Processor Speed: 2.5 GHz Number of Processors: 1 Memory: 16 GB

Versions

The experiment is written in C++14, compiled with Clang 11.0.0

Contents

function:

18 functions for optimization

genetic_algorithm:

implementing genetic algorithm to find best solution for optimal function value.

differiential_evolution:

implementing differential evolution algorithm with 10 different strategies to find best solution for optimal function value.

particle_swamp:

implementing particle swamp algorithm to find best solution for optimal function value.

cuckoo_search:

implementing cuckoo saerch algorithm to find best solution for optimal function value. Basic cuckoo search with improved pa values of three strategies.

whale:

implementing whale optimization algorithm to find best solution for optimal function value.

result

including results and analyzation

Meta

Cheng Su – chengsu6561@gmail.com https://github.com/safrannn/optimization

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different algorithms to find population close to the optimal fitness, including genetic algorithm, differential evolution algorithm, PSO, firefly algorithm, cuckoo search algorithm and whale optimization algorithm in C++.

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