Decoupling Geometry from Optimization in 2D Irregular Cutting and Packing Problems: an Open-Source Collision Detection Engine
Jeroen Gardeyn, Greet Vanden Berghe, Tony Wauters

TL;DR
This paper introduces an open-source collision detection engine that separates geometric feasibility from optimization in 2D irregular cutting and packing problems, simplifying the development of optimization algorithms.
Contribution
The paper presents a novel collision detection engine that decouples geometry from optimization, enabling focused improvements and easier integration in irregular C&P solutions.
Findings
Provides a high-performance, accurate collision detection engine
Enables independent optimization algorithm development
Open-source implementation available for community use
Abstract
Addressing irregular cutting and packing (C&P) optimization problems poses two distinct challenges: the geometric challenge of determining whether or not an item can be placed feasibly at a certain position, and the optimization challenge of finding a good solution according to some objective function. Until now, those tackling such problems have had to address both challenges simultaneously, requiring two distinct sets of expertise and a lot of research & development effort. One way to lower this barrier is to decouple the two challenges. In this paper we introduce a powerful collision detection engine (CDE) for 2D irregular C&P problems which assumes full responsibility for the geometric challenge. The CDE (i) allows users to focus with full confidence on their optimization challenge by abstracting geometry away and (ii) enables independent advances to propagate to all optimization…
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