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Developing a Facility Location Model for Reducing Costs Before and After Enemy Attack

Received: 19 April 2017     Accepted: 25 May 2017     Published: 28 November 2017
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Abstract

Site selection is one of the main principles of the passive defense. A multiple objective and nonlinear programming formulation which considers the principles of passive defense site selection according to both qualitative and quantitative aspects is proposed in this paper. The aim is to reduce the site selection costs while the security of network formed by the facilities is maximized, and to reduce the costs of the network after being attacked. To solve the proposed model, a GA-TOPSIS method is proposed.

Published in American Journal of Applied Scientific Research (Volume 3, Issue 5)
DOI 10.11648/j.ajasr.20170305.12
Page(s) 56-62
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), 2017. Published by Science Publishing Group

Keywords

Passive Defense, Mathematical Programming, Genetic Algorithm

References
[1] A. Ahmadi-Javid, P. Seyedi, S. S. Syam, A survey of healthcare facility location, Computers & Operations Research, 79 (2017) 223-263.
[2] A. Ahmadi, M. S. Pishvaee, M. R. Akbari Jokar, A survey on multi-floor facility layout problems, Computers & Industrial Engineering, 107 (2017) 158-170.
[3] L. Alçada-Almeida, J. Coutinho-Rodrigues, J. Current, A multiobjective modeling approach to locating incinerators, Socio-Economic Planning Sciences, 43 (2009) 111-120.
[4] O. Berman, A. Gavious, Location of terror response facilities: A game between state and terrorist, European Journal of Operational Research, 177 (2007) 1113-1133.
[5] O. Berman, Q. Wang, Locating a semi-obnoxious facility with expropriation, Computers & Operations Research, 35 (2008) 392-403.
[6] J. A. Bullock, G. D. Haddow, D. P. Coppola, 3 - Hazards, in: Homeland Security (Second Edition), Butterworth-Heinemann, 2018, pp. 45-66.
[7] R. L. Church, R. S. Garfinkel, Locating an obnoxious facility on a network, Transportation science, 12 (1978) 107-118.
[8] R. L. Church, A. T. Murray, Business Site Selection, Location Analysis and GIS, (2008).
[9] K. M. Curtin, R. L. Church, A Family of Location Models for Multiple‐Type Discrete Dispersion, Geographical Analysis, 38 (2006) 248-270.
[10] K. Deb, K. Miettinen, Multiobjective optimization: interactive and evolutionary approaches, Springer Science & Business Media, 2008.
[11] Z. Drezner, H. W. Hamacher, Facility location, Springer-Verlag New York, NY, 1995.
[12] Z. Drezner, H. W. Hamacher, Facility location: applications and theory, Springer Science & Business Media, 2001.
[13] Z. Drezner, G. O. Wesolowsky, Location of multiple obnoxious facilities, Transportation Science, 19 (1985) 193-202.
[14] Z. Drezner, G. O. Wesolowsky, Obnoxious facility location in the interior of a planar network, Journal of Regional Science, 35 (1995) 675-688.
[15] E. Erkut, S. Neuman, Analytical models for locating undesirable facilities, European Journal of Operational Research, 40 (1989) 275-291.
[16] A. Giostri, M. Binotti, E. Macchi, Microalgae cofiring in coal power plants: Innovative system layout and energy analysis, Renewable Energy, 95 (2016) 449-464.
[17] P. Hou, W. Hu, C. Chen, M. Soltani, Z. Chen, Optimization of offshore wind farm layout in restricted zones, Energy, 113 (2016) 487-496.
[18] M. Karbasian, S. Abedi, A Multiple Objective Nonlinear Programming Model for Site Selection of the Facilities Based on the Passive Defense Principles, International Journal of Industrial Engineering and Production Research, 22 (2011) 243-250.
[19] M. Kühmaier, G. Erber, C. Kanzian, F. Holzleitner, K. Stampfer, Comparison of costs of different terminal layouts for fuel wood storage, Renewable Energy, 87, Part 1 (2016) 544-551.
[20] J. Movahedniya, The Principles and Basis of Passive Defense, First Edition ed., Malik Ashtar University of Tech., Tehran, 2007.
[21] A. T. Murray, R. L. Church, R. A. Gerrard, W. S. Tsui, Impact models for siting undesirable facilities, Papers in regional science, 77 (1998) 19-36.
[22] J. Rakas, D. Teodorović, T. Kim, Multi-objective modeling for determining location of undesirable facilities, Transportation Research Part D: Transport and Environment, 9 (2004) 125-138.
[23] B. Roy, Multicriteria methodology for decision aiding, Springer Science & Business Media, 2013.
[24] H. Shamsi, Logistics and Site Selection, First Edition ed., Malik Ashtar University of Tech., Tehran, 2007.
[25] H. Skade, ALFRED WEBER's Theory of the location of industries, in: Nationaløkonomisk Tidsskrift, The University Chicago, Chicago, 1929.
[26] J. H. Sorensen, J. Soderstrom, S. A. Carnes, Sweet for the sour: incentives in environmental mediation, Environmental Management, 8 (1984) 287-294.
[27] A. A. Taleizadeh, S. T. A. Niaki, M.-B. Aryanezhad, A hybrid method of Pareto, TOPSIS and genetic algorithm to optimize multi-product multi-constraint inventory control systems with random fuzzy replenishments, Mathematical and Computer Modelling, 49 (2009) 1044-1057.
[28] G. Wesolowski, The Weber problem: History and perspective, Location Science, 1 (1993) 5-23.
Cite This Article
  • APA Style

    Hasan Hosseini-Nasab, Saeed Abedi. (2017). Developing a Facility Location Model for Reducing Costs Before and After Enemy Attack. American Journal of Applied Scientific Research, 3(5), 56-62. https://doi.org/10.11648/j.ajasr.20170305.12

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    ACS Style

    Hasan Hosseini-Nasab; Saeed Abedi. Developing a Facility Location Model for Reducing Costs Before and After Enemy Attack. Am. J. Appl. Sci. Res. 2017, 3(5), 56-62. doi: 10.11648/j.ajasr.20170305.12

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    AMA Style

    Hasan Hosseini-Nasab, Saeed Abedi. Developing a Facility Location Model for Reducing Costs Before and After Enemy Attack. Am J Appl Sci Res. 2017;3(5):56-62. doi: 10.11648/j.ajasr.20170305.12

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  • @article{10.11648/j.ajasr.20170305.12,
      author = {Hasan Hosseini-Nasab and Saeed Abedi},
      title = {Developing a Facility Location Model for Reducing Costs Before and After Enemy Attack},
      journal = {American Journal of Applied Scientific Research},
      volume = {3},
      number = {5},
      pages = {56-62},
      doi = {10.11648/j.ajasr.20170305.12},
      url = {https://doi.org/10.11648/j.ajasr.20170305.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajasr.20170305.12},
      abstract = {Site selection is one of the main principles of the passive defense. A multiple objective and nonlinear programming formulation which considers the principles of passive defense site selection according to both qualitative and quantitative aspects is proposed in this paper. The aim is to reduce the site selection costs while the security of network formed by the facilities is maximized, and to reduce the costs of the network after being attacked. To solve the proposed model, a GA-TOPSIS method is proposed.},
     year = {2017}
    }
    

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    T1  - Developing a Facility Location Model for Reducing Costs Before and After Enemy Attack
    AU  - Hasan Hosseini-Nasab
    AU  - Saeed Abedi
    Y1  - 2017/11/28
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ajasr.20170305.12
    DO  - 10.11648/j.ajasr.20170305.12
    T2  - American Journal of Applied Scientific Research
    JF  - American Journal of Applied Scientific Research
    JO  - American Journal of Applied Scientific Research
    SP  - 56
    EP  - 62
    PB  - Science Publishing Group
    SN  - 2471-9730
    UR  - https://doi.org/10.11648/j.ajasr.20170305.12
    AB  - Site selection is one of the main principles of the passive defense. A multiple objective and nonlinear programming formulation which considers the principles of passive defense site selection according to both qualitative and quantitative aspects is proposed in this paper. The aim is to reduce the site selection costs while the security of network formed by the facilities is maximized, and to reduce the costs of the network after being attacked. To solve the proposed model, a GA-TOPSIS method is proposed.
    VL  - 3
    IS  - 5
    ER  - 

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Author Information
  • Department of Industrial Engineering, Yazd University, Yazd, Iran

  • Department of Industrial Engineering, Yazd University, Yazd, Iran

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