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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...

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Detalles Bibliográficos
Autores principales: Chen, Shengyong, Zheng, Yujun, Cattani, Carlo, Wang, Wanliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
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.
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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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