Crate bin_packing 

Cut list optimization and bin packing for 1D (linear stock), 2D (sheet stock), and 3D (box) problems.

The crate exposes three shipping entry points by default:

• one_d::solve_1d — cutting stock / linear bin packing. Supports first-fit decreasing, best-fit decreasing, multistart local search, and an exact column-generation backend that reports an LP lower bound.
• two_d::solve_2d — rectangular sheet packing. Supports the MaxRects family (best-area, best-short-side-fit, best-long-side-fit, bottom-left, contact-point), the Skyline family (default and minimum-waste), Guillotine beam search with configurable ranking and split rules (best-short-side-fit, best-long-side-fit, shorter- and longer-leftover-axis, min- and max-area splits), shelf heuristics (NFDH, FFDH, BFDH), and a multistart meta-strategy.
• three_d::solve_3d — rectangular box packing. Supports Extreme Points, Guillotine 3D, layer/wall/column builders, DBLF, volume-sorted baselines, randomized meta-strategies, and a restricted exact backend.

The three-d feature (enabled by default) provides the 3D rectangular box packing module with a 29-algorithm catalog. The legacy three-d-preview alias remains available as a compatibility shim.

The 1D and 2D entry points ship an Auto mode that runs multiple strategies and returns the best candidate, ranked lexicographically by unplaced count, stock / sheet count, waste, and cost (with exact as a secondary tiebreaker for 1D).

Additional capabilities:

• Multiple stock / sheet types per problem, each with its own cost and optional inventory cap. When 1D inventory caps are present, one_d::solve_1d also reports a relaxed-inventory procurement estimate per stock type.
• Per-item rotation control for 2D demands, plus a guillotine_required flag that restricts the solver to guillotine-compatible layouts.
• Kerf and trim modeling for 1D cuts so layouts match physical cut lists.
• Reproducible randomized search via an optional seed.
• Structured BinPackingError variants for input validation, infeasible demands (1D, 2D, and 3D), and unsupported solver configurations.
• metrics blocks with iteration counts, explored states, and diagnostic notes.

All problem, option, solution, and metrics types derive serde::Serialize and serde::Deserialize so they can flow through JSON APIs or other wire formats without wrapping.

Example: 1D cutting stock

use bin_packing::one_d::{CutDemand1D, OneDOptions, OneDProblem, Stock1D, solve_1d};

let problem = OneDProblem {
    stock: vec![Stock1D {
        name: "bar".into(),
        length: 96,
        kerf: 1,
        trim: 0,
        cost: 1.0,
        available: None,
    }],
    demands: vec![
        CutDemand1D { name: "rail".into(), length: 45, quantity: 2 },
        CutDemand1D { name: "brace".into(), length: 30, quantity: 2 },
    ],
};
let solution = solve_1d(problem, OneDOptions::default())?;
println!("stock used: {}", solution.stock_count);

Example: 2D rectangular packing

use bin_packing::two_d::{RectDemand2D, Sheet2D, TwoDOptions, TwoDProblem, solve_2d};

let problem = TwoDProblem {
    sheets: vec![Sheet2D {
        name: "plywood".into(),
        width: 96,
        height: 48,
        cost: 1.0,
        quantity: None,
    }],
    demands: vec![RectDemand2D {
        name: "panel".into(),
        width: 24,
        height: 18,
        quantity: 4,
        can_rotate: true,
    }],
};
let solution = solve_2d(problem, TwoDOptions::default())?;
println!("sheets used: {}", solution.sheet_count);

Modules

one_d

One-dimensional cutting stock solvers.

three_d

Three-dimensional rectangular bin packing solvers.

two_d

Two-dimensional rectangular bin packing solvers.

Enums

BinPackingError

Errors returned by the bin-packing solvers.

Type Aliases

Result

Convenient Result alias that uses BinPackingError as the error type.