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Initializer.py

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import numpy as np

def initialization(problem):

# Empty Solution Template

empty_solution = problem['ProblemStructure']

# Extract Problem Info

CostFunction = problem['CostFunction']

VarMin = problem['VarMin']

VarMax = problem['VarMax']

nVar = problem['nVar']

# Create Initial Population

initialpop = []

for i in range(0, 200):

#print(i)

initialpop.append(empty_solution.copy())

#initialpop[i]['position'] = np.random.uniform(VarMin, VarMax, nVar)

initialpop[i]['position'] = np.random.uniform(low=VarMin, high=VarMax, size=(nVar[0], nVar[1]))

#pop=initialpop[i].copy()

initialpop[i] = CostFunction(initialpop[i],problem)

#if "ProblemPosition" in empty_solution:

# gbest['ProblemPosition'] = pop[i]['ProblemPosition'].copy()

initialpop.sort(key=lambda x: x['cost'])

return initialpop