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1

A Multi-label Transformation Framework for the Rectangular 2D Strip-Packing Problem

Neuenfeldt Júnior Alvaro, Francescatto Matheus, Stieler Gabriel, Disconzi David

Management and Production Engineering Review

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2021

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Vol. 14, No. 4

27--37

EN

The present paper describes a methodological framework developed to select a multi-label dataset transformation method in the context of supervised machine learning techniques. We explore the rectangular 2D strip-packing problem (2D-SPP), widely applied in industrial processes to cut sheet metals and paper rolls, where high-quality solutions can be found for more than one improvement heuristic, generating instances with multi-label behavior. To obtain single-label datasets, a total of five multi-label transformation methods are explored. 1000 instances were generated to represent different 2D-SPP variations found in real-world applications, labels for each instance represented by improvement heuristics were calculated, along with 19 predictors provided by problem characteristics. Finally, classification models were fitted to verify the accuracy of each multi-label transformation method. For the 2D-SPP, the single-label obtained using the exclusion method fit more accurate classification models compared to the other four multi-label transformation methods adopted.

2

Features extraction system for automatic speech recognition core mapping into an irregular Network on Chip

Dziurzański P., Mąka T.

Elektronika : konstrukcje, technologie, zastosowania

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2012

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Vol. 53, nr 9

154-156

EN

In this paper, we propose a mapping scheme of IP cores into irregular Network on Chips using an example module dedicated to features extraction for automatic speech recognition system. We estimated the core sizes for various frame sizes and overlappings, and then tried to place cores communicating heavily close to each other, we test a number of widths in the 2D Rectangular Strip Packing problem. The obtained result range allows us to pick a solution that is beneficial both in terms of area and transfers between the system cores.

PL

W artykule zaproponowano sposób mapowania rdzeni IP w nieregularną sieć wewnątrzukładową. Jako przykładowego układu użyto moduł przeznaczony do ekstrakji cech systemu automatycznego rozpoznawania mowy. Dokonano estymacji rozmiaru rdzeni dla różnych rozmiarów ramki i zakładkowania, a następnie dokonano próby odwzorowania rdzeni do układu w ten sposób, by rdzenie wysyłające między sobą duże porcje danych zostały umieszczone blisko siebie.

3

A SAT-based Method for Solving the Two-dimensional Strip Packing Problem

Soh T., Tamura N., Banbara M., Inouey K., Nabeshima H.

Fundamenta Informaticae

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2010

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Vol. 102, nr 3/4

467-487

EN

We propose a satisfiability testing (SAT) based exact approach for solving the twodimensional strip packing problem (2SPP). In this problem, we are given a set of rectangles and one large rectangle called a strip. The goal of the problem is to pack all rectangles without overlapping, into the strip by minimizing the overall height of the packing. Although the 2SPP has been studied in Operations Research, some instances are still hard to solve. Our method solves the 2SPP by translating it into a SAT problem through a SAT encoding called order encoding. The translated SAT problems tend to be large; thus, we apply several techniques to reduce the search space by symmetry breaking and positional relations of rectangles. To solve a 2SPP, that is, to compute the minimum height of a 2SPP, we need to repeatedly solve similar SAT problems. We thus reuse learned clauses and assumptions from the previously solved SAT problems. To evaluate our approach, we obtained results for 38 instances from the literature and made comparisons with a constraint satisfaction solver and an ad-hoc 2SPP solver.