Hi Markus, thanks for the response. I am sorry to intrude, but I do have another question. There is a test problem in <http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page506.htm>. I used the constraint function you pointed me to. I defined a matrix Ain(dimension 9x13) and the vector bin(dimension 9x1) to write the function return value: valid all(Ain*x<=bin). However, the optimum parameters stray by a huge amount from the expected results. The problem has hard boundaries, as well as linear inequality constraints (9 of them to be precise). I hope you can briefly walk me through the correct formulation of the problem in your files, as I suspect my constraints are at the core of the problem.
Hi Markus, does your algorithm allow the inclusion of linear constraints? I am trying to optimize an instance of density evolution, and the parameters must add up to 1. Also, a linear combination of the parameters must yield a given rate. Do you have anything similar to the tools provided by Matlab's global optimization toolbox or do I just have to work around with the parameters, taking the linear constraints into account as I go along?