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Pull Request — master (#202)
by Grega
01:02
created

run_msde   A

↳ Parent: Project

Complexity

Total Complexity 0

Size/Duplication

Total Lines 19
Duplicated Lines 0 %

Importance

Changes 0
Metric Value
eloc 12
dl 0
loc 19
rs 10
c 0
b 0
f 0
wmc 0
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# encoding=utf8
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# This is temporary fix to import module from parent folder
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# It will be removed when package is published on PyPI
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import sys
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sys.path.append('../')
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# End of fix
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import random

            


            
                                                        
            
                                    
            
            

                
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from NiaPy.algorithms.basic import MultiStrategyDifferentialEvolution

            


            
                                                        
            
                                    
            
            

                
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from NiaPy.util import StoppingTask, OptimizationType

            


            
                                                        
            
                                    
            
            

                
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from NiaPy.benchmarks import Sphere

            


            
                                                        
            
                                    
            
            

                
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#we will run Differential Evolution for 5 independent runs

            


            
                                                        
            
                                    
            
            

                
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for i in range(5):

            


            
                                                        
            
                                    
            
            

                
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    task = StoppingTask(D=10, nFES=1000, optType=OptimizationType.MINIMIZATION, benchmark=Sphere())

            


            
                                                        
            
                                    
            
            

                
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    algo = MultiStrategyDifferentialEvolution(NP=50, F=0.5, CR=0.9)

            


            
                                                        
            
                                    
            
            

                
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    best = algo.run(task=task)

            


            
                                                        
            
                                    
            
            

                
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    print('%s -> %s' % (best[0].x, best[1]))

            


            
                                                        
            
                                    
            
            

                
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