Business users can now determine the best course of action under real-world constraints and uncertainty, with input ...

Abstract: In this article, we study the event-triggered distributed optimization problem of second-order nonlinear multiagent systems under undirected and connected communication topologies. To reduce ...

Abstract: Recently, recurrent neural network (RNN) models have been extensively investigated for addressing time-dependent nonlinear optimization problems. However, few existing RNN models take ...

HiOp is an optimization solver for solving certain mathematical optimization problems expressed as nonlinear programming problems. HiOp is a lightweight HPC solver that leverages application's ...

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 ...

Theseus is an efficient application-agnostic library for building custom nonlinear optimization layers in PyTorch to support constructing various problems in robotics and vision as end-to-end ...

Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent ...

Department of Computing, Imperial College London, London, SW7 2AZ, U.K. Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all ...