A cell formation algorithm: Hypergraph approximation - Cut tree

Date

1998-09-16

Author

Kandiller, L

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

138
views

0
downloads

A new cell formation technique is presented and analyzed in this paper. The cell formation problem is defined using the hypergraph representation of the manufacturing systems. The proposed method approximates the hypergraph model by graphs so that the cuts are less affected by the approximation. Consequently, a Gomory-Hu cut tree of the graph approximation is obtained. The minimum cuts between all pairs of vertices are calculated easily by means of this tree, and a partition tree is produced. Our cell formation algorithm successively cuts the partition tree. The algorithm is subjected to an experimentation of randomly generated manufacturing situations. The algorithm is compared with other cell formation techniques as well. (C) 1998 Published by Elsevier Science B.V. All rights reserved.

Subject Keywords

Manufacturing, Modeling, Cell formation, Graph theory, Hypergraphs

URI

https://hdl.handle.net/11511/63666

Journal

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

DOI

https://doi.org/10.1016/s0377-2217(97)00143-4

Collections

Department of Industrial Engineering, Article

Suggestions

OpenMETU
Core

An Information theoretic representation of brain connectivity for cognitive state classification using functional magnetic resonance imaging Önal, Itır; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2013) In this study, a new method for analyzing and representing the discriminative information, distributed in functional Magnetic Resonance Imaging (fMRI) data, is proposed. For this purpose, a local mesh with varying size is formed around each voxel, called the seed voxel. The relationships among each seed voxel and its neighbors are estimated using a linear regression equation by minimizing the expectation of the squared error. This squared error coming from linear regression is used to calculate various info...
A Detailed Analysis for the Absorption Coefficient of Multilevel Uncooled Infrared Detectors Küçük, Serhat; Akın, Tayfun (2011-04-29) This paper introduces a detailed analysis on the calculation of the absorption coefficient of multilevel uncooled infrared detectors. The analysis is carried out considering a two-level 25 mu m pixel pitch infrared detector with a sandwich type resistor which is divided into sub-regions consisting of different stacks of layers. The absorption coefficients of these different sub-regions are calculated individually by using the cascaded transmission line model, including the main body, arms, and the regions w...
Cutting edge: Role of toll-like receptor 9 in CpG DNA-induced activation of human cells Takeshita, F; Leifer, CA; Gursel, I; Ishii, KJ; Takeshita, S; Gürsel, Mayda; Klinman, DM (The American Association of Immunologists, 2001-10-01) Unmethylated CpG motifs present in bacterial DNA stimulate a rapid and robust innate immune response. Human cell lines and PBMC that recognize CpG DNA express membrane-bound human Toll-like receptor 9 (hTLR9). Cells that are not responsive to CpG DNA become responsive when transfected with hTLR9. Expression of hTLR9 dramatically increases uptake of CpG (but not control) DNA into endocytic vesicles. Upon cell stimulation, hTLR9 and CpG DNA are found in the same endocytic vesicles. Cells expressing hTLR9 are ...
A sequential classification algorithm for autoregressive processes Otlu, Güneş; Candan, Çağatay; Çiloğlu, Tolga; Department of Electrical and Electronics Engineering (2011) This study aims to present a sequential method for the classification of the autoregressive processes. Different from the conventional detectors having fixed sample size, the method uses Wald’s sequential probability ratio test and has a variable sample size. It is shown that the suggested method produces the classification decisions much earlier than fixed sample size alternative on the average. The proposed method is extended to the case when processes have unknown variance. The effects of the unknown pro...
A New Decision Fusion Technique for Image Classification Ozay, Mete; Vural, Fatos Tunay Yarman (2009-11-10) In this study, we introduce a new image classification technique using decision fusion. The proposed technique, called Meta-Fuzzified Yield Value.(Meta-FYV), is based on two-layer Stacked Generalization (SG) architecture [1]. At the base-layer, the system, receives a set of feature vectors of various dimensions and dynamical ranges and outputs hypotheses through fuzzy transformations. Then, the hypotheses created by the base layer transformations are concatenated for building a regression equation at meta-l...

Citation Formats

L. Kandiller, “A cell formation algorithm: Hypergraph approximation - Cut tree,” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, pp. 686–702, 1998, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/63666.