Solving Constrained Convex Optimization Problems Using Gradient Descent

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Li Qing 2022-1-26

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https://ww2.mathworks.cn/matlabcentral/answers/1636470-solving-constrained-convex-optimization-problems-using-gradient-descent

评论： Li Qing 2022-1-27

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?

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Torsten 2022-1-26

Try fmincon.

Li Qing 2022-1-27

Thanks!

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Answer 1

Alan Weiss 2022-1-26

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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