"There's beauty to be seen, but here it comes by way of trying to do something useful."
It's easy to take for granted the manufacturing systems that provide us with everything from circuit boards to battleships. This summer, Professor Mike Veatch and student researcher Olivia Gray ’14 are investigating how manufacturing systems and other networks can become "clogged." The problem is that the networks have too many states of congestion to consider them all. Their goal? To develop an optimization model that finds the best schedule for randomly generated jobs. They are also seeking “robust” measures of congestion that get at the worst that is likely to happen.
Dr. Veatch hopes to integrate Olivia's findings into a National Science Foundation grant proposal this fall for more extensive research on robust optimization, which mathematically models planning for worst-case events.
Down the hall on the second floor of the Ken Olsen Science Center, Juliann Booth ’15 is engaged in summer math research of a slightly different sort. In physics and other fields, there is often a need to generate random numbers that follow some pattern. She is learning an ingenious method, Markov chain Monte Carlo, that works even when you don’t have a complete formula for the pattern. Juliann hopes to develop a computer tool using this method that can solve global optimization problems. Her faculty mentor Professor Jon Senning notes that in applied math like Juliann's project, "there's beauty to be seen; here it comes by way of trying to do something useful."