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A Mixed-Integer Linear Programming Formulation for Optimizing Multi-Scale Material and Energy Integration
Frontiers
This research presents a mathematical formulation for optimizing integration of complex industrial systems from the level of unit operations to processes,...
2 days ago
DeepMind & Google Use Neural Networks to Solve Mixed Integer Programs
Synced | AI Technology & Industry Review
Linear programming is used to maximize or minimize a linear objective function subject to one or more constraints, while mixed integer...
34 months ago
AI accelerates problem-solving in complex scenarios | MIT News | Massachusetts Institute of Technology
MIT News
Researchers from MIT and ETZ Zurich have developed a new, data-driven machine-learning technique that speeds up software programs used to...
6 months ago
Mixed integer programs, adversarial attacks, and graph neural networks
INDIAai
These are the most intriguing AI research pieces published this year.
17 months ago
Faster sorting algorithms discovered using deep reinforcement learning
Nature
Fundamental algorithms such as sorting or hashing are used trillions of times on any given day1. As demand for computation grows,...
12 months ago
Reinforcement Learning to Approximate Mixed-Integer Allocation Solutions on Simulated Data
Towards Data Science
Note: This project is not affiliated with any organization in terms of source code or data. This is a personal project that I developed from...
20 months ago
Zero-One Integer Programming Meaning and Examples
Investopedia
Zero-one integer programming is a mathematical method of using a series of yes (1) and no (0) answers to arrive at a solution.
87 months ago
What do you think about improving metaheuristics using mathematical programming?
ResearchGate
In recent years, many new heuristic algorithms are proposed in the community. However, it seems that they are already following a similar...
41 months ago
Accelerating transmission-constrained unit commitment via a data-driven learning framework
Frontiers
As a fundamental task in power system operations, transmission-constrained unit commitment (TCUC) decides ON/OFF state (i.e.,...
21 months ago
Google & Lund U’s Optimus Learned Optimization Architecture Efficiently Captures Complex Dependencies
Synced | AI Technology & Industry Review
Solving optimization problems is crucial for real-world AI applications ranging from capital market investment to neural network training.
18 months ago