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

The previous article in this series examined how institutions misclassify AI‑driven exposure due to legacy metrics, ...

Abstract: This article considers the problem of designing a continuous-time dynamical system that solves a constrained nonlinear optimization problem and makes the feasible set forward invariant and ...

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 ...

This paper presents the Secant Optimization Algorithm (SOA), a novel mathematics-inspired metaheuristic derived from the Secant Method. SOA enhances search efficiency by repeating vector updates using ...

The rapidly growing computational demands of artificial intelligence (AI) and complex optimization tasks are increasingly straining conventional electronic architectures, driving the search for novel, ...

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 ...

PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's renowned derivative-free optimization methods, i ...

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 ...

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 ...