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Searching Crease Patterns by Genetic Algorithm for Origami Design
Conference paper

Searching Crease Patterns by Genetic Algorithm for Origami Design

Meng-Huan Lu, Yu-Wei Wen and Chuan-Kang Ting
2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
2022

Abstract

Crease pattern genetic algorithm orthogonal structure representation Artificial Intelligence Computer Science Applications Computational Mathematics Control and Optimization
Origami is a folding technique that can be used to create paper models. This technique has diverse applications in art, engineering, and medical devices, such as tessellations, deployable structures, and venous stents. Recently, a number of approaches have been developed to generate crease patterns for desired paper models. Most of the existing methods are specially designed to handle one or a few certain types of topologies and thus have limited applicability. To address this issue, this study proposes a genetic algorithm (GA) to generate crease patterns for orthogonal-structure origami models. Two crease pattern representations, i.e., string and matrix, are designed for the GA to deal with crease pattern search. The experimental results on three test instances indicate that the GA is capable of finding the target crease patterns. In particular, the string representation leads to faster convergence than the matrix representation. These outcomes show the potential of GA for origami design.

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