An open-source heuristic to reboot 2D nesting research

2025-09-05

arXiv.org

AI Summary

The two-dimensional irregular strip packing problem suffers from stagnant research progress, poor reproducibility, and underestimated optimization potential. To address these challenges, this paper introduces Sparrow, an open-source heuristic solver. Its core innovation is the “sequential feasibility decomposition” framework, which hierarchically decomposes the global optimization problem into a series of collision-free feasibility subproblems, integrating efficient collision detection, geometric processing, and heuristic search strategies. We release ten real-world industrial benchmark instances and fully open-source the implementation. Experimental results demonstrate that Sparrow significantly outperforms state-of-the-art methods across multiple benchmarks, achieving simultaneous improvements in nesting quality and computational efficiency. By establishing a transparent, reproducible, and extensible foundation, Sparrow breaks longstanding technical barriers and fosters sustainable academic advancement in irregular packing research.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Solvers and Tools
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

2D nesting problems rank among the most challenging cutting and packing problems. Yet, despite their practical relevance, research over the past decade has seen remarkably little progress. One reasonable explanation could be that nesting problems are already solved to near optimality, leaving little room for improvement. However, as our paper demonstrates, we are not at the limit after all. This paper presents $ exttt{sparrow}$, an open-source heuristic approach to solving 2D irregular strip packing problems, along with ten new real-world instances for benchmarking. Our approach decomposes the optimization problem into a sequence of feasibility problems, where collisions between items are gradually resolved. $ exttt{sparrow}$ consistently outperforms the state of the art - in some cases by an unexpectedly wide margin. We are therefore convinced that the aforementioned stagnation is better explained by both a high barrier to entry and a widespread lack of reproducibility. By releasing $ exttt{sparrow}$'s source code, we directly address both issues. At the same time, we are confident there remains significant room for further algorithmic improvement. The ultimate aim of this paper is not only to take a single step forward, but to reboot the research culture in the domain and enable continued, reproducible progress.

Problem

• Solving 2D irregular strip packing problems with open-source heuristic
• Overcoming research stagnation in 2D nesting through reproducible methods
• Developing new benchmarks and approaches for cutting and packing optimization

Innovation

• Open-source heuristic for 2D irregular strip packing
• Decomposes optimization into sequential feasibility problems
• Releases source code to address reproducibility barriers