Optimizer

run(optimizer, objectivefunc, dataset_List, NumOfRuns, params, export_flags): 

It serves as the main interface of the framework for running the experiments.
    
Parameters
----------    
optimizer : list
    The list of boolean preference of optimizers
objectivefunc : list
    The list of boolean preference of objective functions
dataset_List : list
    The list of the names of the data sets files
NumOfRuns : int
    The number of independent runs 
params  : set
    The set of parameters which are: 
    1. Size of population (PopulationSize)
    2. The number of iterations (Iterations)
export_flags : set
    The set of Boolean flags which are: 
    1. Export (Exporting the results in a file)
    2. Export_details (Exporting the detailed results in files)

Returns
-----------
N/A
    

selector(algo,func_details, k, f, popSize,Iter, points)

This is used to call the algorithm which is selected

Parameters
----------
algo : int
     The index of the selected algorithm
func_details : dict
     consists of the details of the selected function
k : int
     Number of clusters
f : int
     Number of features
popSize : int
     Size of population (the number of individuals at each iteration)
Iter : int
     The number of iterations
points : numpy.ndaarray
     The attribute values of all the points

Returns
-----------
obj
     x: solution object returned by the selected algorithm