Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
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Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 143
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 209
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3051
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
Severity: Warning
Message: Attempt to read property "Count" on bool
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File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3053
Function: _error_handler
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
This paper proposes dynamic mixed integer facility location model to design an international manufacturing network (IMN). The proposed model considers a broad facility network linking production and distribution facilities located internationally. The proposed model discussed in the paper assumes significance over the traditional manufacturing model as it provides a country specific analysis making it more convenient for the decision maker to devise country specific strategies within an international ecosystem. Therefore, the model considers import export cost, loan subsidies along with depreciation expense and other operating costs applicable to specific country. The objective of the model is to identify optimal facility locations and the production distribution in the entire network to meet the demand of global markets. The proposed model is illustrated and computationally tested using two cases. Model parameters are mapped using 3Vs of Big Data viz. Volume, Velocity and Variety.
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http://dx.doi.org/10.1016/j.scitotenv.2019.135549 | DOI Listing |
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