Randomized search heuristics (e.g., evolutionary algorithms, simulated annealing etc.) are very appealing to practitioners, they are easy to implement and usually provide good per...
Abstract—In the real world, many applications are nonstationary optimization problems. This requires that optimization algorithms need to not only find the global optimal soluti...
In this paper, we show the optimality of a certain class of disturbance-affine control policies in the context of one-dimensional, constrained, multi-stage robust optimization. Ou...
Dimitris Bertsimas, Dan Andrei Iancu, Pablo A. Par...
Hybrid algorithms that combine genetic algorithms with the Nelder-Mead simplex algorithm have been effective in solving certain optimization problems. In this article, we apply a s...
Praveen Koduru, Sanjoy Das, Stephen Welch, Judith ...
In this paper we present a method of parameter optimization, relative trust-region learning, where the trust-region method and the relative optimization [21] are jointly exploited...