Paper Info
Title
Modeling of biological intelligence for SCM system optimization.
Abstract
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.
Year
DOI
Venue
2012
10.1155/2012/769702
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Keywords
Field
DocType
intelligence,algorithms
Evolutionary algorithm,Computational intelligence,Computer science,Swarm intelligence,System optimization,Differential evolution,Supply chain management,Artificial intelligence,Evolutionary programming,Genetic algorithm,Machine learning
Journal
Volume
ISSN
Citations 
2012
1748-670X
16
PageRank 
References 
Authors
0.81
44
4
Name
Order
Citations
PageRank
Sheng-Yong Chen11077114.06
Yujun Zheng237628.53
Carlo Cattani39226.22
Wan-Liang Wang423539.16