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A Study in Pairwise Clustering for Bi-dimensional Irregular Strip Packing Using the Dotted Board Model

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Author(s):
Sato, Andre Kubagawa ; Setter Bauab, Guilherme Elias ; Martins, Thiago de Castro ; Guerra Tsuzuki, Marcos de Sales ; Gomes, Antonio Miguel
Total Authors: 5
Document type: Journal article
Source: IFAC PAPERSONLINE; v. 51, n. 11, p. 6-pg., 2018-01-01.
Abstract

The bi-dimensional irregular strip packing is a difficult problem in the cutting and packing field. Its main feature, and central source of complexity, is the irregularity of the shape of the items. Consequently, mathematical solvers are only able to obtain optimal solutions for small instances and heuristics are often employed in the literature. In such algorithms, it is not possible to guarantee that the optimum solution is found. In such cases, a restricted version of the problem can be adopted in order to improve the performance. One possible restriction is the adoption of pairwise clustering, i.e., elimination of items by joining two pieces. In this work, an automatic pairwise clustering method is proposed for the dotted board model, which limits the placement of items to equally distributed discrete points. The clustered problems are then used as input to an irregular strip packing solver. The results obtained in this paper can be used as an initial guideline for the use of clustering in a discrete grid, which was beneficial in some of the tested cases. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 10/18913-4 - Study about no-fit polygons translations to create degenerated collision free regions through non regularized Boolean operations
Grantee:Marcos de Sales Guerra Tsuzuki
Support Opportunities: Regular Research Grants
FAPESP's process: 10/19646-0 - Translating No-Fit Polygons to Create Degenerated Collision Free Region Using Non-Regulerized Boolean Operations
Grantee:André Kubagawa Sato
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 13/26532-9 - Massive parallel algorithm development with GPGPU to create discrete obstructive region mountain
Grantee:Marcos de Sales Guerra Tsuzuki
Support Opportunities: Regular Research Grants