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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/15478

Title: Origami Folding Sequence Generation Using Discrete Particle Swarm Optimization
Authors: Bui, Ha-Duong
Jeong, Sungmoon
Chong, Nak Young
Mason, Matthew
Keywords: mathematical origami
folding sequence
combinatorial optimization
particle swarm optimization
Issue Date: 2017-10-24
Publisher: Springer
Magazine name: Lecture Notes in Computer Science
Volume: 10637
Start page: 484
End page: 493
DOI: 10.1007/978-3-319-70093-9_51
Abstract: This paper proposes a novel approach to automating origamior paper folding. The folding problem is formulated as a combinatorial optimization problem to automatically find feasible folding sequences toward the desired shape from a generic crease pattern, minimizing the dissimilarity between the current and desired origami shapes. Specifically, we present a discrete particle swarm optimization algorithm, which can take advantage of the classical particle swarm optimization algorithm in a discrete folding action space. Through extensive numerical experiments, we have shown that the proposed approach can generate an optimum origami folding sequence by iteratively minimizing the Hausdorff distance, a dissimilarity metric between two geometric shapes. Moreover, an in-house origami simulator is newly developed to visualize the sequence of origami folding.
Rights: This is the author-created version of Springer, Ha-Duong Bui, Sungmoon Jeong, Nak Young Chong, Matthew Mason, Lecture Notes in Computer Science, 10637, 2017, 484-493. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-319-70093-9_51
URI: http://hdl.handle.net/10119/15478
Material Type: author
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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