Solving a MINLP Optimization Problem
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I have a mixed integer nonlinear optimization problem containing "log" function, and by the way it's convex if we relaxed the integer variables.
Can I solve it using Matlab Optimization toolbox efficiently or there will be some issues?
Is there a difference in solving such optimization problems if I used problem-based and used solver-based approaches?
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Accepted Answer
Alan Weiss
on 10 Aug 2021
There are two MINLP solvers in Global Optimization Toolbox:
ga
and
surrogateopt
. Either should work for you. The
surrogateopt
solver is primarily for time-consuming functions. Both solvers work best on relatively low-dimensional problems, up to 100 variables or so, but there are no built-in limits, so you can try larger problems.
There is also an example showing how
intlinprog
can sometimes be used iteratively to solve otherwise convex mixed-integer problems:
Mixed-Integer Quadratic Programming Portfolio Optimization: Problem-Based
or the nearly identical
Mixed-Integer Quadratic Programming Portfolio Optimization: Solver-Based
.
Good luck,
Alan Weiss
MATLAB mathematical toolbox documentation
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