Orientation

Reading for Martin Luther King Day

Assignments (note: due dates are subject to change)

Course Notes

Matlab functions for optimization

These Matlab functions implement methods for minimizing a function of several parameters subject to a set of inequality constraints:
minimize f(x) such that g(x) ≤ 0,
where x is a vector of design variables, f(x) is a scalar-valued objective function, and g(x) is a vector of constraints.

Matlab functions for random variables

These Matlab functions can be used to compute probability distribution functions and to generate samples of random variables.
Distribution PDF, fX(x) CDF, FX(x) inverse CDF, FX-1(p) generate sample, x1 ... xN
uniform unifpdf.m unifcdf.m unifinv.m rand.m
triangular triangular_pdf.m triangular_cdf.m triangular_inv.m triangular_rnd.m
normal normpdf.m normcdf.m norminv.m randn.m
log-normal logn_pdf.m logn_cdf.m logn_inv.m logn_rnd.m
Poisson Poisson_pmf.m Poisson_cdf.m Poisson_rnd.m
exponential exp_pdf.m exp_cdf.m exp_inv.m exp_rnd.m
Rayleigh Rayleigh_pdf.m Rayleigh_cdf.m Rayleigh_inv.m Rayleigh_rnd.m
gamma gamma_pdf.m gamma_cdf.m gamma_inv.m gamma_rnd.m
Laplace Laplace_pdf.m Laplace_cdf.m Laplace_inv.m Laplace_rnd.m
GEV GEV_pdf.m GEV_cdf.m GEV_inv.m GEV_rnd.m
The m-file MCS_intro.m illustrates the use of a number of these functions.

Additional References

© 2001-2020 Henri P. Gavin; updated: 9-27-2001, 12-15-2003, 1-7-2004, 1-6-2005, 1-22-2005, 2-1-2005, 2-14-2005, 1-11-2006, 2-14-2008, 2-28-2008, 3-24-2008, 1-8-2009, 8-7-2009, 1-5-2011, 1-8-2014, 1-7-2015, 1-13-2016, 1-10-2020