With a little less than 1 year to finish my PhD, the chief complaint from my advisor about my project is that, while my methodology has produced very good results, I have applied it to only one problem domain: Portfolio Optimization. While I have been making analysis and hybrids of my technique that have given me small differential gains in performance, what I really need is to find out other problem domains where I could apply my technique, to demonstrate its generality.

Unfortunately, it is not so easy as it seems. My MTGA, in short, was made for bounded parameter optimization problems. This means a problem that can be described as: “you have a value, X, which must be divided among Y variables (sum of all Y is X)”. The problem is that most benchmark functions for parameter optimization are not bounded. I have to assign the values of Y, but they are not bounded by an X sum. I tried to get around that by adding a “dump” variable which would get the remaining value of X, but that breaks down because I still need to know the max X, negative values make everything go wonky.

In my current research, X is the total resource available for investiment, and Y are the different assets that I can invest that resource into. If you can describe your research problem (in any field, no need to be remotely related to computing) in terms of this X and Y, I would love to hear about it!