Write a function to find the values of a design variable vector, x, that minimizes a scalar objective function, f, given a function handle to f, a starting guess, x0, subject to inequality and equality constraints with function handles g<=0 and h=0, respectively. Use a quadratic exterior penalty for the sequential unconstrained minimization technique (SUMT) with an optional input vector of penalty parameter values that become increasingly larger.
Solution Stats
Problem Comments
Solution Comments
Show commentsProblem Recent Solvers14
Suggested Problems
-
Project Euler: Problem 6, Natural numbers, squares and sums.
2586 Solvers
-
Back to basics 2 - Function Path
185 Solvers
-
Remove white space from the string
208 Solvers
-
176 Solvers
-
Generate a vector like 1,2,2,3,3,3,4,4,4,4
14383 Solvers
More from this Author17
Problem Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Please, be aware that test cases don't necessarily use all the same penalty parameters. For instance, I have used 1e6 for cases 2,3,4 & 6 and 1e4 for cases 1 & 5. It all depends on which method one uses for the exterior penalty (and approximations may fail because of it).
In a sense, it is like trying to find the secret formula instead of finding the minimum value of a function.