Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
This paper discusses product variety design under optimization viewpoint. Product variety design means the challenge to simultaneously design multiple products toward higher optim...
We introduce a convex relaxation framework to optimally
minimize continuous surface ratios. The key idea is to minimize
the continuous surface ratio by solving a sequence
of con...
Kalin Kolev (University of Bonn), Daniel Cremers (...
This paper proposes an equation-based multi-scenario iterative robust optimization methodology for analog/mixed-signal circuits. We show that due to local circuit performance mono...