Modeling of Biological Intelligence for SCM System Optimization

Joint Authors

Wang, Wanliang
Zheng, Yujun
Cattani, Carlo
Chen, Sheng-yong

Source

Computational and Mathematical Methods in Medicine

Issue

Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2011-11-24

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Medicine

Abstract EN

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.

American Psychological Association (APA)

Chen, Sheng-yong& Zheng, Yujun& Cattani, Carlo& Wang, Wanliang. 2011. Modeling of Biological Intelligence for SCM System Optimization. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-497365

Modern Language Association (MLA)

Chen, Sheng-yong…[et al.]. Modeling of Biological Intelligence for SCM System Optimization. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-10.
https://search.emarefa.net/detail/BIM-497365

American Medical Association (AMA)

Chen, Sheng-yong& Zheng, Yujun& Cattani, Carlo& Wang, Wanliang. Modeling of Biological Intelligence for SCM System Optimization. Computational and Mathematical Methods in Medicine. 2011. Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-497365

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-497365