---
language: en
license: mit
tags:
- operations-research
- decomposition
- method-selection
- enterprise
- aria-ai
library_name: decompbench
---

# DecompBench Method Selector

Feature-calibrated method selector for large-scale optimization decomposition.

## Intended Use

Recommends a decomposition strategy (Benders, Dantzig-Wolfe, Column Generation, Lagrangian, Progressive Hedging, ADMM) from instance structure features.

## Input Features

- `n_master_variables`, `n_sub_variables`, `n_coupling_constraints`
- `n_scenarios`, `block_angularity`, `constraint_density`, `decomposability_score`

## Artifacts

- `selector_weights.json` — scoring weights
- `config.json` — model metadata

## Limitations

Calibrated on synthetic instances. Validate on production models before deployment.

## Space

https://huggingface.co/spaces/alirezaaminzadeh/large-scale-optimization-decomposition-lab