This award was started in the academic year 2016/2017. The merit of the thesis is assessed by a committee consisting of 5 experts in the area of OR, which includes both academics and practitioners. The committee found all the nominated theses worthy of recognition and of high quality.

Among those, Benjamin’s thesis stood out for its high quality both from a theoretically and practical standpoint. His thesis was well-structured and professional. This is not a simple task to achieve when one takes into consideration the complexity of his topic.

As his adviser Stein W. Wallace explains in his nomination letter, the thesis handles the problem of generating scenarios for stochastic programs where the distribution is somehow complicated. More specifically, his work branches into areas where nothing but pure sampling could possibly work. And pure sampling is too weak for large problems in all realistic settings. Benjamin very elegantly expands the set of distributions that can be handled efficiently in stochastic programs. So, in fact, the thesis is very practical.

All the potential of his work is now being exploited for his PhD work at NHH, where he is using his expertise to handling uncertain problems in fish-farming, where the problems at hand are very large and random variables complicated. We congratulate Benjamin for this prize and wish him the best with his PhD work, which we are sure will keep up with the high standards of his master thesis.

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