[Solved] Identify the error in this code for nonlinear constraint optimization: from scipy.optimize import minimize def obj(x): return x[0]**2 + x[1]**2 constraint = {'type': 'eq', 'fun': lambda x:... | SciPy

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Identify the error in this code for nonlinear constraint optimization:

from scipy.optimize import minimize

def obj(x):
    return x[0]**2 + x[1]**2

constraint = {'type': 'eq', 'fun': lambda x: x[0] + x[1] - 1}

result = minimize(obj, [0, 0], constraints=constraint, method='SLSQP')
print(result.x)

AInitial guess violates the equality constraint

BConstraint type should be 'ineq' instead of 'eq'

CObjective function must be linear

DMethod 'SLSQP' does not support constraints

Step-by-Step Solution

Solution:

Step 1: Check initial guess against constraint
Initial guess [0,0] does not satisfy x[0] + x[1] = 1.
Step 2: Understand impact on solver
Starting point violating equality constraints can cause solver to fail or converge slowly.
Final Answer:
Initial guess violates the equality constraint -> Option A
Quick Check:
Initial guess must satisfy equality constraints [OK]

Quick Trick: Start with guess satisfying equality constraints [OK]

Common Mistakes:

Using wrong constraint type
Assuming objective must be linear
Thinking SLSQP can't handle constraints

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Identify the error in this code for nonlinear constraint optimization:

Step 1: Check initial guess against constraint

Step 2: Understand impact on solver

Final Answer:

Quick Check:

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