ware_ops_pipes

Python Version License

ware_ops_pipes is a library for automated and context aware pipeline synthesis of warehouse operations problems. Together with ware_ops_algos, ware_ops_pipes forms the meta-model framework Data Driven Decisions for Logistics (3D4L).

Framework Overview

The 3D4L framework consists of four main components:

🏭 Data Layer and Domain Objects (ware_ops_algos)

To deal with heterogenous data sources, warehouse information is organized into domain objects: Layout, Articles, Orders, Resources, and Storage.

🛠️ Algorithm Repository (ware_ops_algos)

Modular implementations of algorithms for item assignment, batching, routing, and scheduling. Each algorithm is annotated with its requirements via algorithm cards.

⚙️ Domain-Algorithm Mapping (ware_ops_algos)

Filtering mechanism that identifies applicable algorithms based on instance characteristics and algorithm requirements.

🔄 Context-aware Pipelines (ware_ops_pipes)

Uses CLS-Luigi to automatically generate all feasible algorithm combinations as directed acyclic graphs.

3D4L Architecture

Architecture of the 3D4L framework.

Quick Start

📘 Getting Started

Start here with a basic introduction to 3D4L.

Run 3D4L on a Single Instance
📚 API Documentation

Detailed API reference for all modules and classes.

API Reference
💡 Examples

Examples and benchmark evaluations.

Examples

Citation

If you use ware_ops_pipes in your research, please cite:

@misc{bischoff2026ware_ops_pipes,
 author = {Bischoff, Janik and Suba, Oezge Nur and Barlang, Maximilian and Kutabi, Hadi and Mohring, Uta and Dunke, Fabian and Meyer, Anne and Nickel, Stefan and Furmans, Kai},
 title = {ware_ops_pipes},
 year = {2026},
 publisher = {GitHub},
 journal = {GitHub Repository},
 howpublished = {\url{https://github.com/kit-dsm/ware_ops_pipes.git}},

}

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