langkhachhoha/MPaGE

[AAAI-26] MPaGE: Pareto-Grid-Guided Large Language Models for Fast and High-Quality Heuristics Design in Multi-Objective Combinatorial Optimization

28
/ 100
Experimental

This tool helps researchers and practitioners in combinatorial optimization automatically design efficient heuristics for complex problems with multiple competing objectives, like finding the shortest delivery routes while minimizing fuel costs. It takes problem definitions and desired optimization goals as input, then uses advanced AI to generate and refine problem-solving strategies, outputting a set of high-quality, diverse heuristics. This is ideal for operations researchers, logistics planners, or anyone tackling multi-objective optimization challenges.

Use this if you need to rapidly develop and test new, high-performing heuristics for multi-objective combinatorial optimization problems without extensive manual design.

Not ideal if your problem involves single-objective optimization or if you require direct control over every line of the heuristic's code rather than an automated generation process.

operations-research logistics-optimization supply-chain-management resource-allocation algorithm-design
No License No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 7 / 25
Community 4 / 25

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Language

Python

License

Last pushed

Mar 10, 2026

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