| Peer-Reviewed

A Novel Strategy for Comparative Points in Facility Layout Problem with Fuzzy Logic

Received: 4 May 2015     Accepted: 1 July 2015     Published: 6 July 2015
Views:       Downloads:
Abstract

Distance measure is one of the most important component in facility layout problems. Many distance approaches have been proposed so far. However, there is no method that can always give a satisfactory solution to every situation. In this paper, first we review on some distance methods, then we present a new strategy for comparative points in facility layout with fuzzy logic, which it is very useable, specifically when it is hard (or impossible) to use other methods to solve uncertain points. Finally, some numerical examples illustrate the presented method as well as comparing it with other various ones.

Published in International Journal of Management and Fuzzy Systems (Volume 1, Issue 2)
DOI 10.11648/j.ijmfs.20150102.11
Page(s) 15-20
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Multi Attribute Decision Making (MADM), Facility Layout (FL), Distance Measure, Fuzzy Logic,Uncertain Points, MOER Method, Decision Making (DM)

References
[1] Agarwal C. C., and. Yu, P. S., (2008), editors. Privacy Preserving Data Mining: Models and Algorithms. Springer.
[2] Agarwal, P. K., Cheng, S.-W., Tao, Y., and Yi K., (2009), Indexing uncertain data. Proceedings of ACM Principals of Database Systems.
[3] Agarwal, P. K., Har-Peled, S., and Varadarajan, K. R., (2004), Approximating extent measure of points. Journal of ACM 51(4).
[4] Agarwal, P. K., Har-Peled, S., and Varadarajan, K., (2007), Geometric approximations via coresets. C. Trends Comb. and Comp. Geom. (E. Welzl).
[5] Agarwal, P. K., Procopiuc, C. M., and Varadarajan. K. R., (2002), Approximation algorithms for k-line center. Proceedings European Symposium on Algorithms, pp. 54-63.
[6] Agarwal, R., and Srikant, R., (2000), Privacy-preserving data mining. ACM SIGMOD Record 29:439-450.
[7] Agrawal, P., Benjelloun, O., Sarma, A. D., Hayworth, C., Nabar, S., Sugihara, T., and Widom, J., (2006), Trio: A system for data, uncertainty, and lineage. Proceedings ACM Principals of Database Systems.
[8] Ali Beigi, M., Hajjari, T., Ghasem Khani, E., (2015), A New Index For Fuzzy Distance Measure, Appl. Math. Inf. Sci. 9, No. 6, 1-9.
[9] Bloch, I., (1999), On fuzzy distances and their use in image processing under imprecision, Pattern Recognition, vol.32, pp.1873-1895.
[10] Cha, S., and Srihari, S. N., (2002), On Measuring the Distance between Histograms, in Pattern Recognition, Vol 35/6, pp 1355-1370.
[11] Deza E. and Deza M.M., (2006), Dictionary of Distances, Elsevier.
[12] Deza, M-M., and Deza, E., Encyclopedia of Distances, (online http://www.sciencedirect.com/science/book/9780444520876) by Elsevier.
[13] Dubois, D., and Prade, H., (1978), Operation on fuzzy numbers, International Journal of Systems Science, vol.9, pp.613-626.
[14] Fachao, L., Lianqing, S., Xiangdong, Y.,and Jiqing, Q., (2001), The absolute value of fuzzy number and its basic properties, The Journal of Fuzzy Mathematics 9, pp403-412.
[15] Floudas, CH-A., Pardalos, P-M., (2009), Optimizing Facility Location with Euclidean and Rectilinear Distances, Springer US, Online ISBN 978-0-387-74759-0.
[16] Francis, R.L., White, J.A., McGinnis, F., (1992) , Facility Layout and Location: an Analytical Approach, Prentic-Hall.
[17] Gavin D.G., Oswald W.W., Wahl, E.R., and Williams J.W., (2003), A statistical approach to evaluating distance metrics and analog assignments for pollen records, Quaternary Research 60, pp 356–367.
[18] Gilbert, E. N., and Pollak, H. 0., (1968), Steiner minimal tree, this Journal, 16, pp. 1-29.
[19] Grabusts, P., (2011), THE CHOICE OF METRICS FOR CLUSTERING ALGORITHMS, Environment. Technology. Resources Proceedings of the 8th International Scientific and Practical Conference. Volume I1.
[20] HANAN, M., (1966), On Steiner's problem with rectilineardistance, this Journal, 14, pp. 255-265.
[21] Jahantigh, M. A., and Hajighasemi, S., (2012), Ranking of generalized fuzzy numbers using distance measure and similarity measure, International Journal of Industrial Mathematics, 4, 405-416.
[22] Jamshidi, M., Titli, A., Zadeh, L.A, Boverie, S., (Eds.), (1997), Applications of Fuzzy Logic – Towards High Machine Intelligence Quotient Systems, Environmental and Intelligent Manufacturing Systems Series, vol. 9, Prentice Hall, Upper Saddle River, NJ.
[23] Kailath, T., (1967), The divergence and bhattacharyya distance measures in signal selection, IEEE Trans. Commun. Technol. COM-15 (1) 52–60.
[24] KRUSKAL, J. B., (1956), On the shortest spanning subtree of a graph, Proc. Amer. Math. Soc., 7, pp. 48-50.
[25] MELZAK, Z. A., (1961), On the problem of Steiner, Canad. Math. Bull., 4, pp. 143-148.
[26] Monev V., (2004), Introduction to Similarity Searching in Chemistry, MATCH Commun. Math. Comput. Chem. 51 pp. 7-38.
[27] Pedrycz, W., (2007), Collaborative and knowledge-based fuzzy clustering, International journal of Innovating computing, Information and Control, Vol.3, no.1, pp.1-12.
[28] PRIM, R. C., (1957), Shortest connecting networks, Bell System Tech. J., 31, pp. 1398-1401.
[29] Saha, P.K., Wehrli, F.W., and Gomberg, B. R., (2001), Fuzzy Distance Transform: Theory, Algorithms and Applications, Computer Vision and Image Understanding, vol. 86, pp.171-190.
[30] Voxman, W., (1998), Some remarks on distances between fuzzy numbers, Fuzzy Sets and Systems, vol.100, pp.353-365.
[31] Yang, Y. Y., and Wing, O., (1972), Optimal and suboptimal solution algorithms for the wiring problem, Proc. IEEE Internat. Symp. Circuit Theory, pp. 154-158.
[32] Zadeh, L.A., (1975), Fuzzy logic and approximate reasoning, Synthese 30, 407–428.
[33] Zadeh, L.A., (1979), A theory of approximate reasoning, in: J. Hayes, D. Michie, L.I. Mikulich (Eds.), Machine Intelligence 9, Halstead Press, New York, pp. 149–194.
[34] Zadeh, L.A., (2008), Is there a need for fuzzy logic?, Information Sciences 178, 2751–2779.
[35] Zezula P., Amato G., Dohnal V., and Batko M., (2006), Similarity Search The Metric Space Approach, Springer.
Cite This Article
  • APA Style

    Erfan Ghasem Khani, Mostafa Ali Beigi. (2015). A Novel Strategy for Comparative Points in Facility Layout Problem with Fuzzy Logic. International Journal of Management and Fuzzy Systems, 1(2), 15-20. https://doi.org/10.11648/j.ijmfs.20150102.11

    Copy | Download

    ACS Style

    Erfan Ghasem Khani; Mostafa Ali Beigi. A Novel Strategy for Comparative Points in Facility Layout Problem with Fuzzy Logic. Int. J. Manag. Fuzzy Syst. 2015, 1(2), 15-20. doi: 10.11648/j.ijmfs.20150102.11

    Copy | Download

    AMA Style

    Erfan Ghasem Khani, Mostafa Ali Beigi. A Novel Strategy for Comparative Points in Facility Layout Problem with Fuzzy Logic. Int J Manag Fuzzy Syst. 2015;1(2):15-20. doi: 10.11648/j.ijmfs.20150102.11

    Copy | Download

  • @article{10.11648/j.ijmfs.20150102.11,
      author = {Erfan Ghasem Khani and Mostafa Ali Beigi},
      title = {A Novel Strategy for Comparative Points in Facility Layout Problem with Fuzzy Logic},
      journal = {International Journal of Management and Fuzzy Systems},
      volume = {1},
      number = {2},
      pages = {15-20},
      doi = {10.11648/j.ijmfs.20150102.11},
      url = {https://doi.org/10.11648/j.ijmfs.20150102.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmfs.20150102.11},
      abstract = {Distance measure is one of the most important component in facility layout problems. Many distance approaches have been proposed so far. However, there is no method that can always give a satisfactory solution to every situation. In this paper, first we review on some distance methods, then we present a new strategy for comparative points in facility layout with fuzzy logic, which it is very useable, specifically when it is hard (or impossible) to use other methods to solve uncertain points. Finally, some numerical examples illustrate the presented method as well as comparing it with other various ones.},
     year = {2015}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - A Novel Strategy for Comparative Points in Facility Layout Problem with Fuzzy Logic
    AU  - Erfan Ghasem Khani
    AU  - Mostafa Ali Beigi
    Y1  - 2015/07/06
    PY  - 2015
    N1  - https://doi.org/10.11648/j.ijmfs.20150102.11
    DO  - 10.11648/j.ijmfs.20150102.11
    T2  - International Journal of Management and Fuzzy Systems
    JF  - International Journal of Management and Fuzzy Systems
    JO  - International Journal of Management and Fuzzy Systems
    SP  - 15
    EP  - 20
    PB  - Science Publishing Group
    SN  - 2575-4947
    UR  - https://doi.org/10.11648/j.ijmfs.20150102.11
    AB  - Distance measure is one of the most important component in facility layout problems. Many distance approaches have been proposed so far. However, there is no method that can always give a satisfactory solution to every situation. In this paper, first we review on some distance methods, then we present a new strategy for comparative points in facility layout with fuzzy logic, which it is very useable, specifically when it is hard (or impossible) to use other methods to solve uncertain points. Finally, some numerical examples illustrate the presented method as well as comparing it with other various ones.
    VL  - 1
    IS  - 2
    ER  - 

    Copy | Download

Author Information
  • Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin, Iran

  • Young Researchers and Elite Club, Islamic Azad University, Firoozkooh, Iran

  • Sections