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Modeling of Biological Intelligence for SCM System Optimization
This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related m...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3227372/ https://www.ncbi.nlm.nih.gov/pubmed/22162724 http://dx.doi.org/10.1155/2012/769702 |
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author | Chen, Shengyong Zheng, Yujun Cattani, Carlo Wang, Wanliang |
author_facet | Chen, Shengyong Zheng, Yujun Cattani, Carlo Wang, Wanliang |
author_sort | Chen, Shengyong |
collection | PubMed |
description | This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. |
format | Online Article Text |
id | pubmed-3227372 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-32273722011-12-08 Modeling of Biological Intelligence for SCM System Optimization Chen, Shengyong Zheng, Yujun Cattani, Carlo Wang, Wanliang Comput Math Methods Med Review Article This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. Hindawi Publishing Corporation 2012 2011-11-24 /pmc/articles/PMC3227372/ /pubmed/22162724 http://dx.doi.org/10.1155/2012/769702 Text en Copyright © 2012 Shengyong Chen et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Chen, Shengyong Zheng, Yujun Cattani, Carlo Wang, Wanliang Modeling of Biological Intelligence for SCM System Optimization |
title | Modeling of Biological Intelligence for SCM System Optimization |
title_full | Modeling of Biological Intelligence for SCM System Optimization |
title_fullStr | Modeling of Biological Intelligence for SCM System Optimization |
title_full_unstemmed | Modeling of Biological Intelligence for SCM System Optimization |
title_short | Modeling of Biological Intelligence for SCM System Optimization |
title_sort | modeling of biological intelligence for scm system optimization |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3227372/ https://www.ncbi.nlm.nih.gov/pubmed/22162724 http://dx.doi.org/10.1155/2012/769702 |
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