awesome-fm4co and awesome-ml4co

awesome-fm4co
51
Established
awesome-ml4co
45
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 15/25
Maintenance 6/25
Adoption 10/25
Maturity 8/25
Community 21/25
Stars: 486
Forks: 39
Downloads:
Commits (30d): 0
Language:
License: MIT
Stars: 2,087
Forks: 233
Downloads:
Commits (30d): 0
Language: Python
License:
No Package No Dependents
No License No Package No Dependents

About awesome-fm4co

ai4co/awesome-fm4co

Recent research papers about Foundation Models for Combinatorial Optimization

This is a curated collection of research papers that explore how Foundation Models, especially Large Language Models (LLMs), can be used to solve complex combinatorial optimization problems. It helps researchers and practitioners understand the latest advancements in using AI to find optimal solutions or improve existing algorithms for tasks like supply chain planning or vehicle routing. The collection categorizes papers based on whether they use existing LLMs or build domain-specific Foundation Models.

operations-research supply-chain-optimization vehicle-routing scheduling algorithm-design

About awesome-ml4co

Thinklab-SJTU/awesome-ml4co

Awesome machine learning for combinatorial optimization papers.

This resource is a curated list of academic papers that explore how machine learning can be applied to solve complex combinatorial optimization problems. It takes research on various optimization challenges like vehicle routing, scheduling, or resource allocation, and provides references to papers using machine learning techniques. Operations researchers, industrial engineers, and data scientists seeking advanced methods to optimize real-world processes would find this valuable.

operations-research logistics-optimization scheduling resource-allocation algorithm-design

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