Description of the algorithms used in the implementations of
MMA and GCMMA in Matlab.
Files for both MMA and GCMMA:
============================
subsolv.m
kktcheck.m
toy1.m
toy2.m
subsolv.m
=========
The function subsolv.m makes an attempt to solve either
the MMA subproblem generated by mmasub.m,
or the GCMMA subproblem generated by gcmmasub.m.
A straight-forward primal-dual interior-point method is used.
kktcheck.m
==========
The function kktcheck.m calculates the left hand sides of the
KKT conditions for the optimization problem defined by the user.
toy1.m and toy2.m
=================
Define, together with mmatoyinit.m or gctoyinit.m, the users problem.
----------------------------------------------------------------
Files for MMA only:
==================
mmasub.m
mmatoymain.m
mmatoyinit.m
mmatoyresults
mmasub.m
========
The function mmasub.m generates the MMA subproblem for
the current iteration, and calls the function subsolv.m
mmatoymain.m
============
The file mmatoymain.m makes an attempt to solve the users
optimization problem which is defined by the files
mmatoyinit.m and toy2.m.
In each MMA iteration, mmatoymain.m calls toy2.m and mmasub.m.
----------------------------------------------------------------
Files for GCMMA only:
====================
gcmmasub.m
asymp.m
concheck.m
raaupdate.m
gctoymain.m
gctoyinit.m
gctoyresults
gcmmasub.m
==========
The function gcmmasub.m generates the GCMMA subproblem for the
current outer/inner iteration, and calls the function subsolv.m.
asymp.m
===========
The function asymp.m calculates values on the parameters raa0, raa,
low and upp in the beginning of each outer GCMMA iteration.
concheck.m
===========
The function concheck.m checks if the current GCMMA
approximations are sufficiently conservative.
raaupdate.m
===========
The function raaupdate.m updates the parameters raa0 and raa
in each inner iteration.
gctoymain.m
===========
The file gctoymain.m makes an attempt to solve the users
optimization pr
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