How can one optimize a multivariate function by differential_evolution

Question

I would like to optimize a multivariate function by differential evolution using lambda function. Actually the parameters based on which I want to optimize the function are matrices each of which has a different dimension. this is my code:

R0= [[(0,1)]]
Q0=[[(0,1)]]
c0= (0,1)
beta0=[[(-6,9)]] 
B0=[ (-2,2),(-2,2),(-2,2),(-2,2),(-2,2),(-2,2),    (-2,2),(-2,2),(-2,2),(-2,2),(-2,2),(-2,2),(-2,2),(-2,2)]
B0=np.array([B0])
B0=B0.T

kal_=lambda R,Q,c,beta,B:myfunc(R,Q,c,beta,B,Y,X)
opt=scipy.optimize.differential_evolution(kal_(R0,Q0,c0,beta0,B0), maxiter=1000000,tol=1e-6)

Python returns the following error which is due to the bounds set as the initial values:

ValueError: setting an array element with a sequence.

Can anyone let me know what is wrong with the code?