[Solved] What will be the value of result.success after running this code?from scipy.optimize import minimize obj = lambda x: x[0]**2 + x[1]**2 cons = [{'type': 'eq', 'fun': lambda x: x[0] - 1}, {'type':... | SciPy

SciPy - Advanced Optimization

What will be the value of result.success after running this code?

from scipy.optimize import minimize

obj = lambda x: x[0]**2 + x[1]**2
cons = [{'type': 'eq', 'fun': lambda x: x[0] - 1}, {'type': 'ineq', 'fun': lambda x: x[1] - 1}]
result = minimize(obj, [0, 0], constraints=cons)
print(result.success)

ANone

BFalse

CRaises an error

DTrue

Step-by-Step Solution

Solution:

Step 1: Analyze constraints and objective
Objective minimizes sum of squares. Constraints fix x0=1 and require x1>=1.
Step 2: Check feasibility and optimization result
Starting at [0,0], optimizer can find feasible point [1,1] with objective 2. Optimization should succeed.
Final Answer:
True -> Option D
Quick Check:
Feasible constraints lead to success = True [OK]

Quick Trick: Check if constraints allow feasible solution [OK]

Common Mistakes:

Assuming failure due to initial guess
Confusing eq and ineq constraints
Expecting error without syntax issues

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What will be the value of result.success after running this code?

Step 1: Analyze constraints and objective

Step 2: Check feasibility and optimization result

Final Answer:

Quick Check:

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