Constrained optimization.

I went about making my optimal decision by using a technique called linear programming. Linear programming is a mathematical optimization technique that can be used to find the optimal solution to a problem with a set of constraints. In this case, the constraints were the amount of money that I had to invest and my risk tolerance. The objective was to maximize the expected return on my investment. I used a linear programming software to solve the problem. The software found the optimal portfolio of stocks to invest in, given my constraints. The optimal portfolio had an expected return of 10%, and it was within my risk tolerance. I was satisfied with the results, and I felt that I had achieved optimality. I knew that I had achieved optimality because the software had found the solution that maximized the expected return, given my constraints. There was no other portfolio of stocks that would have given me a higher expected return, given my constraints. I believe that constrained optimization is a valuable tool that can be used to make better decisions. In this case, it helped me to find the optimal portfolio of stocks to invest in, given my constraints. This helped me to achieve my financial goals, and I was satisfied with the results.