Solving Constrained Convex Optimization Problems Using Gradient Descent

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The paper only says that the optimal value can be obtained by the gradient descent method. I downloaded some code about gradient descent on MATLAB, and the objective functions are relatively simple, such as f = x^2 + y^2 + 5, and the optimization problems are all unconstrained. How can I solve the following problem using gradient descent? Is there an example to refer to?

Accepted Answer

Alan Weiss
Alan Weiss on 26 Jan 2022
That problem does not look unconstrained to me: you have two sets of constraints listed.
But the main point is twofold: there is no built-in code for gradient descent in Optimization Toolbox™, but there are several solvers (such as fmincon, which Torsten mentioned) that can address constrained nonlinear optimization problems.
You might find the Problem-Based Optimization Workflow to be the most natural way to formulate and solve your problem.
Good luck,
Alan Weiss
MATLAB mathematical toolbox documentation

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