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AI-based optimization method achieves breakthrough in ethylene manufacturing: higher profits and reduced carbon emissions

The latest study published in Engineering has unveiled a groundbreaking approach to advancing green ethylene manufacturing, with profound implications for global sustainable chemical production.
Scientific Research Publishing

Adby, P. (2013) Introduction to Optimization Methods. Springer Science & Business Media.

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
IEEE

Task Assignment and Exploration Optimization for Low Altitude UAV Rescue via Generative AI Enhanced Multi-agent Reinforcement Learning

Abstract: The integration of emerging uncrewed aerial vehicle (UAV) with artificial intelligence (AI) and ground-embedded robots (GERs) has transformed emergency rescue operations in unknown ...
insideHPC

IonQ and Kipu Quantum Report Protein Folding and Optimization Problem Records

KARLSRUHE, Germany and COLLEGE PARK, Md.– Kipu Quantum and IonQ (NYSE: IONQ) announced what they said is a record achievement: the successful solution of “the most complex known protein folding ...
IEEE

Distributed Aggregative Optimization Algorithm for Solving Multirobot Formation Problem

Abstract: This article investigates a distributed aggregative optimization problem, focusing on formation control within local constraint sets over a multirobot system. Each robot's local objective ...
marktechpost

REDA: A Novel AI Approach to Multi-Agent Reinforcement Learning That Makes Complex Sequence-Dependent Assignment Problems Solvable

Power distribution systems are often conceptualized as optimization models. While optimizing agents to perform tasks works well for systems with limited checkpoints, things begin to go out of hand ...