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- % Decision Variables
- cvx_begin
- variables xsb xre xc xs
-
- % Objective Function
- maximize(0.04*xsb + 0.06*xre + 0.08*xc + 0.09*xs)
-
- % Constraints
- subject to
- xsb + xre + xc + xs == 2.5e6
- xc + xs <= 2*xsb
- xs <= xc
- xc <= 1.7*xre
- xsb >= 0
- xre >= 0
- xc >= 0
- xs >= 0
- cvx_end
-
- % Display the optimal solution
- fprintf('Optimal Solution:\n');
- fprintf('State Bonds: %.1f euros\n', xsb);
- fprintf('Real Estate Loans: %.1f euros\n', xre);
- fprintf('Car Loans: %.1f euros\n', xc);
- fprintf('Scholarship Loans: %.1f euros\n', xs);
- import cvxpy as cp
-
- # Decision Variables
- xsb = cp.Variable()
- xre = cp.Variable()
- xcℓ = cp.Variable()
- xsℓ = cp.Variable()
-
- # Objective Function
- objective = cp.Maximize(0.04*xsb + 0.06*xre + 0.08*xcℓ + 0.09*xsℓ)
-
- # Constraints
- constraints = [
- xsb + xre + xcℓ + xsℓ == 2.5e6,
- xcℓ + xsℓ <= 2*xsb,
- xsℓ <= xcℓ,
- xcℓ <= 1.7*xre,
- xsb >= 0,
- xre >= 0,
- xcℓ >= 0,
- xsℓ >= 0
- ]
-
- # Solve the problem
- problem = cp.Problem(objective, constraints)
- problem.solve()
-
- # Display the optimal solution
- print("Optimal Solution:")
- print(f"State Bonds: {xsb.value:.1f} euros")
- print(f"Real Estate Loans: {xre.value:.1f} euros")
- print(f"Car Loans: {xcℓ.value:.1f} euros")
- print(f"Scholarship Loans: {xsℓ.value:.1f} euros")
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