Journal article Open Access

Green Supply Chain Management Optimization Based On NSGA-II Method

S. Sundar; C. Dhanasekaran; S. Sivaganesan


Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Blue Eyes Intelligence Engineering  &amp; Sciences Publication (BEIESP)</dc:contributor>
  <dc:creator>S. Sundar</dc:creator>
  <dc:creator>C. Dhanasekaran</dc:creator>
  <dc:creator>S. Sivaganesan</dc:creator>
  <dc:date>2019-12-30</dc:date>
  <dc:description>Green Supply Chain Management (GSCM) is the adopted by many companies due to the government policies of various countries. The optimization technique can be applied in the GSCM to increase the profit of the company. In this research, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) technique is applied for the optimization of GSCM to increase the performance. The NSGA-II method has the advantage of choosing the solution closer to the pareto-solution and uses the elitist technique to preserve the best solution in the next generation. Mathematical model of the GSCM system is established and data is provided as input to the mathematical mode. Data is generated in three types, small scale, medium scale and large scale. The proposed NSGA-II method has high performance in the optimization technique compared to existing method. The proposed NSGA-II method has the Number of Pareto Solution (NPS) metrics of 17 for large scale data, while existing method has 14.</dc:description>
  <dc:identifier>https://zenodo.org/record/5598657</dc:identifier>
  <dc:identifier>10.35940/ijeat.B3092.129219</dc:identifier>
  <dc:identifier>oai:zenodo.org:5598657</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>issn:2249-8958</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:source>International Journal of Engineering and Advanced Technology (IJEAT) 9(2) 210-216</dc:source>
  <dc:subject>Green Supply Chain Management, Non-dominated Sorting Genetic Algorithm -II, Elitist technique, Mathematical model, and Number of Pareto Solution.</dc:subject>
  <dc:subject>ISSN</dc:subject>
  <dc:subject>Retrieval Number</dc:subject>
  <dc:title>Green Supply Chain Management Optimization  Based On NSGA-II Method</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
</oai_dc:dc>
14
16
views
downloads
Views 14
Downloads 16
Data volume 10.6 MB
Unique views 14
Unique downloads 16

Share

Cite as