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A Novel Space Partitioning Algorithm to Improve Current Practices in Facility Placement.

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Title: A Novel Space Partitioning Algorithm to Improve Current Practices in Facility Placement.
Authors: Jimenez, Tamara1, Mikler, Armin R.1, Tiwari, Chetan1
Source: IEEE Transactions on Systems, Man & Cybernetics: Part A. Sep2012, Vol. 42 Issue 5, p1194-1205. 12p.
Subjects: Public health research, Mathematical optimization, Reaction time, Epidemics, Pandemics, Algorithms
Abstract: In the presence of naturally occurring and man-made public health threats, the feasibility of regional bio-emergency contingency plans plays a crucial role in the mitigation of such emergencies. While the analysis of in-place response scenarios provides a measure of quality for a given plan, it involves human judgment to identify improvements in plans that are otherwise likely to fail. Since resource constraints and government mandates limit the availability of service provided in case of an emergency, computational techniques can determine optimal locations for providing emergency response assuming that the uniform distribution of demand across homogeneous resources will yield an optimal service outcome. This paper presents an algorithm that recursively partitions the geographic space into subregions while equally distributing the population across the partitions. For this method, we have proven the existence of an upper bound on the deviation from the optimal population size for subregions. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Transactions on Systems, Man & Cybernetics: Part A is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
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  Data: <searchLink fieldCode="DE" term="%22Public+health+research%22">Public health research</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Reaction+time%22">Reaction time</searchLink><br /><searchLink fieldCode="DE" term="%22Epidemics%22">Epidemics</searchLink><br /><searchLink fieldCode="DE" term="%22Pandemics%22">Pandemics</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
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  Data: In the presence of naturally occurring and man-made public health threats, the feasibility of regional bio-emergency contingency plans plays a crucial role in the mitigation of such emergencies. While the analysis of in-place response scenarios provides a measure of quality for a given plan, it involves human judgment to identify improvements in plans that are otherwise likely to fail. Since resource constraints and government mandates limit the availability of service provided in case of an emergency, computational techniques can determine optimal locations for providing emergency response assuming that the uniform distribution of demand across homogeneous resources will yield an optimal service outcome. This paper presents an algorithm that recursively partitions the geographic space into subregions while equally distributing the population across the partitions. For this method, we have proven the existence of an upper bound on the deviation from the optimal population size for subregions. [ABSTRACT FROM PUBLISHER]
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  Data: <i>Copyright of IEEE Transactions on Systems, Man & Cybernetics: Part A is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/TSMCA.2012.2183360
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 1194
    Subjects:
      – SubjectFull: Public health research
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Reaction time
        Type: general
      – SubjectFull: Epidemics
        Type: general
      – SubjectFull: Pandemics
        Type: general
      – SubjectFull: Algorithms
        Type: general
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      – TitleFull: A Novel Space Partitioning Algorithm to Improve Current Practices in Facility Placement.
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            NameFull: Jimenez, Tamara
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              M: 09
              Text: Sep2012
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              Y: 2012
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            – TitleFull: IEEE Transactions on Systems, Man & Cybernetics: Part A
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