In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

Abstract: In this paper, a two-layer recurrent neural network is proposed to solve the nonsmooth convex optimization problem subject to convex inequality and linear equality constraints. Compared with ...

Cart-pole swing-up: Find the force profile to apply to the cart to swing-up the pendulum that freely hanges from it. Compute the gait (joint angles, rates, and torques) for a walking robot that ...

The U.S. military experienced logistics challenges with land-locked Afghanistan, but one of the last times it faced actively contested logistics was with the German submarine wolfpacks in World War II ...

ReHLine-Python is the official Python implementation of ReHLine, a powerful solver for large-scale empirical risk minimization (ERM) problems with convex piecewise linear-quadratic (PLQ) loss ...

To fully tap the abilities of renewables in reactive power optimization, this paper develops a detailed model for the power regulation capabilities of wind turbines and photovoltaic units and studies ...

Abstract: This note investigates a network optimization problem in which a group of agents cooperate to minimize a global function under the practical constraint of finite-bandwidth communication. We ...

A team of computer scientists has come up with a dramatically faster algorithm for one of the oldest problems in computer science: maximum flow. The problem asks how much material can flow through a ...

Center on Stochastic Modeling, Optimization, and Statistics (COSMOS), The University of Texas at Arlington, Arlington, TX, USA. Quantitative decision analysis involves notions of comparison and ...