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Write a function to find the values of a design variable vector, *x*, that minimizes a scalar objective function, *f* ( *x* ), given a function handle to *f*, and a starting guess, *x0*, subject to inequality constraints *g* ( *x* )<=0 with function handle *g*. Use a logarithmic interior penalty for the sequential unconstrained minimization technique (SUMT) with an optional input vector of increasing penalty parameter values. That is, the penalty (barrier) function, *P*, is

P(x,r) = -sum(log(-g(x)))/r

where *r* is the penalty parameter.

6 correct solutions
7 incorrect solutions

Last solution submitted on May 14, 2015