Jerome Chong <jeromechong <at> gmail.com> writes: > > Greetings, > > What I want to do is to perform regression the data set to get a > revenue function, and use that revenue function to find the maximum > point (maybe with some constraints applied). > The regressed revenue function would most likely be in a quadratic > form (depending on the price-volume data set), and the constraints > most likely will be in linear form. > If I just get the largest product from the data set, it might not give > me the maximum revenue from the revenue function (assuming not > violating any constraints). > To take the constraints into account, won't I be needing non-linear programming? > > And if I expect the variable to be an integer value (say price for > maximized revenue needs to be in integer), I would be requiring mixed > integer programming. > > Is there a single package can I use to handle all these? > > /Jerome > >
This optimization problem is called MINLP for Mixed Integer Nonlinear Programming. Don't know if there are MINLP solvers for R but they are available for other environments (e.g. GAMS). The first part is regression, that is of course very much in the realm of R. ---------------------------------------------------------------- Erwin Kalvelagen Amsterdam Optimization Modeling Group [email protected] http://amsterdamoptimization.com ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
