# U-Nesting
**2D/3D Spatial Optimization Engine** - High-performance nesting and bin packing algorithms in Rust with C FFI support
[](https://crates.io/crates/u-nesting)
[](https://docs.rs/u-nesting)
[](https://github.com/iyulab/U-Nesting/actions)
[](LICENSE)
[](https://www.rust-lang.org/)
<p align="center">
<img src="assets/U-Nesting.gif" alt="U-Nesting Demo" width="800">
</p>
## Overview
U-Nesting provides domain-agnostic spatial optimization algorithms for 2D nesting and 3D bin packing problems:
- **2D Nesting** - Optimal polygon placement on bounded surfaces
- **3D Bin Packing** - Optimal volume arrangement in containers
- **Genetic Algorithm** - Metaheuristic optimization for complex layouts
- **NFP/NFR Computation** - Precise collision-free placement
### Design Philosophy
U-Nesting is a **pure computation engine** with no domain-specific logic. Industry context (manufacturing, textile, logistics, etc.) is determined by consuming applications.
```text
┌─────────────────────────────────────────┐
│ Consuming Applications │
│ (Manufacturing, Textile, Logistics) │
└─────────────────┬───────────────────────┘
│ Domain Context
▼
┌─────────────────────────────────────────┐
│ U-Nesting Engine │
│ Pure Geometry + Optimization Math │
│ (Domain Agnostic) │
└─────────────────────────────────────────┘
```
## Features
- 🚀 **High Performance** - Written in Rust with parallel computation via Rayon
- 🎯 **Domain Agnostic** - Abstract models adaptable to any spatial optimization
- 📐 **2D Support** - Polygon nesting with NFP and holes (curves are supplied as polylines — flatten with a tolerance before submitting)
- 📦 **3D Support** - Box packing with physical constraints (gravity, stability, mass limits)
- 🔌 **C FFI Support** - Use from C#, Python, or any language with C bindings
- 📦 **Zero Domain Dependencies** - Pure mathematical optimization
## Demo
### Sample Dataset
A test dataset with **9 different polygon shapes** and **50 total pieces** on a 500×500 boundary:
<p align="center">
<img src="assets/samples.png" alt="Sample Shapes" width="400">
<img src="assets/random.png" alt="Randomized Order" width="400">
</p>
<p align="center">
<em>Left: Original shapes | Right: Randomized input order</em>
</p>
### Algorithm Comparison
Optimization results using different algorithms on the same dataset (50 pieces, 500×500 boundary, 2 strips):
| **GA** (Genetic Algorithm) | <img src="assets/GA.png" alt="GA Result" width="300"> | **70.6%** | 19.5s |
| **GDRR** (Goal-Driven Ruin & Recreate) | <img src="assets/GDRR.png" alt="GDRR Result" width="300"> | 69.4% | 30.5s |
| **ALNS** (Adaptive Large Neighborhood Search) | <img src="assets/ALNS.png" alt="ALNS Result" width="300"> | 69.1% | 30.2s |
| **NFP** (No-Fit Polygon Guided) | <img src="assets/NFP.png" alt="NFP Result" width="300"> | 68.5% | 5.0s |
| **BRKGA** (Biased Random-Key GA) | <img src="assets/BRKGA.png" alt="BRKGA Result" width="300"> | 67.8% | 23.5s |
| **SA** (Simulated Annealing) | <img src="assets/SA.png" alt="SA Result" width="300"> | 64.1% | 34.3s |
| **BLF** (Bottom-Left Fill) | <img src="assets/BLF.png" alt="BLF Result" width="300"> | 60.0% | 338ms |
> **Note**: Higher utilization = better material efficiency. Results may vary depending on piece shapes, quantities, and constraints. Run your own benchmarks to find the best algorithm for your specific use case.
>
> These figures were captured before 0.11.0. Layouts and times differ from 0.11.0 on, which changed how placement follows the sheet's length, enforces `spacing` and `margin`, and honours `time_limit_ms`.
## Installation
### From crates.io
```toml
[dependencies]
u-nesting = "0.15" # 2D only (default)
u-nesting = { version = "0.15", features = ["3d"] } # 2D + 3D
```
### From GitHub
```toml
[dependencies]
u-nesting = { git = "https://github.com/iyulab/u-nesting" }
```
## Quick Start
### 2D Nesting
```rust
use u_nesting::d2::{Boundary2D, Geometry2D, Nester2D};
use u_nesting::{Config, Solver, Strategy};
// Define geometries to place
let geometries = vec![
Geometry2D::new("G1")
.with_polygon(vec![(0.0, 0.0), (100.0, 0.0), (100.0, 50.0), (0.0, 50.0)])
.with_quantity(5)
.with_rotations_deg(vec![0.0, 90.0, 180.0, 270.0]),
];
// Define boundary
let boundary = Boundary2D::rectangle(1000.0, 500.0);
// Configure and run
let config = Config::new()
.with_strategy(Strategy::NfpGuided)
.with_spacing(3.0)
.with_margin(10.0);
let result = Nester2D::new(config).solve(&geometries, &boundary).unwrap();
assert_eq!(result.placements.len(), 5);
println!("Utilization: {:.1}%", result.utilization * 100.0);
```
### 3D Bin Packing
```rust
use u_nesting::d3::{Boundary3D, Geometry3D, Packer3D};
use u_nesting::{Config, Solver, Strategy};
// Define geometries to place
let geometries = vec![
Geometry3D::new("G1", 30.0, 20.0, 15.0)
.with_quantity(10)
.with_mass(2.5),
];
// Define boundary; gravity and stability are properties of the container
let boundary = Boundary3D::new(120.0, 80.0, 100.0)
.with_max_mass(500.0)
.with_gravity(true)
.with_stability(true);
// Configure and run
let config = Config::new().with_strategy(Strategy::ExtremePoint);
let result = Packer3D::new(config).solve(&geometries, &boundary).unwrap();
assert_eq!(result.placements.len(), 10);
println!("Utilization: {:.1}%", result.utilization * 100.0);
```
## Core Concepts
| **Geometry** | Shape to be placed | Polygon | Box |
| **Boundary** | Containing region | Rectangle, Polygon | Box |
| **Placement** | Position + orientation | x, y, θ | x, y, z, rotation |
| **Spacing** | Minimum distance between two placed geometries | Float | Float |
| **Margin** | Minimum distance from a geometry to the boundary edge | Float | Float |
| **Constraint** | Placement rules | Rotation, Direction | Orientation, Stability |
## Module Structure
```text
u-nesting/
├── core/ # Shared abstractions
│ ├── traits.rs # Geometry, Boundary, Solver
│ ├── ga.rs # Genetic algorithm framework
│ ├── config.rs # Common configuration
│ └── result.rs # Unified result types
│
├── d2/ # 2D Module
│ ├── geometry.rs # Polygon, Point, Segment
│ ├── boundary.rs # 2D boundary definitions
│ ├── nfp.rs # No Fit Polygon
│ ├── nester.rs # Placement algorithms
│ └── io.rs # Import/Export
│
├── d3/ # 3D Module
│ ├── geometry.rs # Box (Geometry3D)
│ ├── boundary.rs # 3D boundary definitions
│ ├── nfr.rs # No Fit Region
│ ├── packer.rs # Placement algorithms
│ ├── physics.rs # Gravity, stability
│ └── io.rs # Import/Export
│
└── ffi/ # C FFI interface
```
## Algorithms
### 2D Algorithms
| **BLF** (Bottom-Left Fill) | Greedy placement at bottom-left positions | ★★★☆☆ | ★★★★★ |
| **NFP** (No-Fit Polygon Guided) | NFP-based collision-free placement | ★★★★☆ | ★★★☆☆ |
| **GA** (Genetic Algorithm) | Sequence optimization with crossover/mutation | ★★★★★ | ★★☆☆☆ |
| **BRKGA** (Biased Random-Key GA) | Random-key encoding with elite inheritance | ★★★★★ | ★★☆☆☆ |
| **SA** (Simulated Annealing) | Temperature-based neighborhood search | ★★★★☆ | ★★★☆☆ |
| **GDRR** (Greedy Descent with Random Restarts) | Local search with restart diversification | ★★★★☆ | ★★★☆☆ |
| **ALNS** (Adaptive Large Neighborhood Search) | Destroy-repair with operator selection | ★★★★★ | ★★☆☆☆ |
### What the 2D heuristic and search strategies guarantee
BLF, NFP, GA, BRKGA, SA, GDRR and ALNS (the optional exact MILP strategies are
not covered here):
- **`spacing`** is the minimum distance between any two placed parts (it may be
exceeded by at most 0.12 %, the allowance for rounded offsets). It does not
apply to the boundary.
- **`margin`** is the minimum distance from any part to every boundary edge,
including slanted edges of a polygon boundary and the edges of holes.
- Parts are placed inside the boundary polygon, never over a hole.
- Layouts advance along the boundary's longer side (the strip's length) and
fill across the shorter one.
- **`time_limit_ms`** bounds the whole solve: the search strategies return the
best layout found within it, plus the time of the bottom-left pass they are
compared against.
- The search strategies (GA, BRKGA, SA, GDRR, ALNS) never return a layout that
places fewer parts, or uses more length, than bottom-left fill on the same
input — nor than greedy NFP placement, whenever that pass completes within
the time limit (it runs first, inside the limit).
### 3D Algorithms
| **Extreme Point** | Placement at extreme points | ★★★☆☆ | ★★★★★ |
| **Layer Packing** | Layer-based bottom-up placement | ★★★☆☆ | ★★★★☆ |
| **Genetic Algorithm** | Sequence and rotation optimization | ★★★★★ | ★★☆☆☆ |
## Configuration
### 2D Configuration
```rust
use u_nesting::{Config, Strategy};
// One `Config` serves 2D and 3D; every setting has a builder method.
let config = Config::new()
.with_spacing(3.0) // Minimum distance between geometries
.with_margin(10.0) // Minimum distance to the boundary edge
.with_strategy(Strategy::GeneticAlgorithm)
.with_time_limit(30_000) // Whole solve, in milliseconds (0 = unlimited)
.with_target_utilization(0.90)
.with_seed(42); // Reproducible runs
```
Rotation and mirroring are per geometry (`Geometry2D::with_rotations_deg`,
`with_flip`), not part of the configuration.
### 3D Configuration
```rust
use u_nesting::d3::geometry::OrientationConstraint;
use u_nesting::d3::{Boundary3D, Geometry3D};
use u_nesting::{Config, Strategy};
let config = Config::new()
.with_margin(5.0) // Boundary wall offset
.with_strategy(Strategy::ExtremePoint)
.with_time_limit(30_000);
// Physics lives on the container, orientation on each geometry.
let boundary = Boundary3D::new(120.0, 80.0, 100.0)
.with_gravity(true)
.with_stability(true);
let item = Geometry3D::new("crate", 30.0, 20.0, 15.0)
.with_orientation(OrientationConstraint::Upright);
```
## FFI Interface
### JSON Request (2D)
```json
{
"mode": "2d",
"geometries": [
{
"id": "G1",
"polygon": [[0,0], [100,0], [100,50], [0,50]],
"quantity": 5,
"rotations": [0, 90, 180, 270]
}
],
"boundary": { "width": 1000, "height": 500 },
"config": { "spacing": 3.0, "strategy": "ga" }
}
```
### JSON Request (3D)
```json
{
"mode": "3d",
"geometries": [
{
"id": "G1",
"dimensions": [30, 20, 15],
"quantity": 10,
"mass": 2.5
}
],
"boundary": { "dimensions": [120, 80, 100], "max_mass": 500 },
"config": { "gravity": true, "stability": true }
}
```
### C Interface
```c
extern int unesting_solve(const char* request_json, char** result_ptr);
extern void unesting_free_string(char* ptr);
```
```csharp
// C# example
[LibraryImport("u_nesting")]
public static partial int unesting_solve(string request, out IntPtr result);
```
## Result Structure
```text
SolveResult {
placements: Vec<Placement>, // Position + orientation for each placed instance
boundaries_used: usize, // Number of boundaries needed
utilization: f64, // Area/volume efficiency (0.0 - 1.0)
unplaced: Vec<String>, // Deduplicated IDs of geometries that couldn't fit
total_requested: usize, // Σ quantity; unplaced instances = total_requested - placements.len()
computation_time_ms: u64,
}
```
## Performance
### 2D Benchmarks (GA, 500 generations)
| 20 | Simple | 200ms | 92% |
| 100 | Mixed | 2s | 88% |
| 500 | Complex | 15s | 85% |
### 3D Benchmarks (Extreme Point)
| 50 | Uniform | 100ms | 85% |
| 200 | Mixed | 1.5s | 78% |
| 100 | Constrained | 3s | 72% |
## Architecture
```text
┌──────────────────────────────────────────────┐
│ U-Nesting Engine │
├──────────────────────────────────────────────┤
│ Core: Traits, GA Framework, Config │
├─────────────────────┬────────────────────────┤
│ 2D Module │ 3D Module │
├─────────────────────┼────────────────────────┤
│ Polygon, NFP │ Box, NFR │
│ BLF, GA Nester │ EP, LAFF, GA Packer │
└─────────────────────┴────────────────────────┘
▲ ▲
│ │
┌─────────┴────────────────────┴───────────────┐
│ Consuming Applications │
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │ Sheet │ │ Mold │ │Container│ ... │
│ │ Metal │ │ Design │ │ Loading │ │
│ └─────────┘ └─────────┘ └─────────┘ │
└──────────────────────────────────────────────┘
```
## License
Licensed under either of:
- MIT license ([LICENSE](LICENSE))
## Contributing
Contributions are welcome! Please read [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
## Related
- [u-numflow](https://github.com/iyulab/u-numflow) — Mathematical primitives
- [u-metaheur](https://github.com/iyulab/u-metaheur) — Metaheuristic optimization (GA, SA, ALNS, CP)
- [u-geometry](https://github.com/iyulab/u-geometry) — Computational geometry
- [u-schedule](https://github.com/iyulab/u-schedule) — Scheduling framework