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.
authors.affiliation: College of Computer Science & Technology, Zhejiang University of Technology, Hangzhou 310023, China. sy@ieee.org
authors.forename: Shengyong
authors.initials: S
authors.lastname: Chen
authors.forename: Yujun
authors.initials: Y
authors.lastname: Zheng
authors.forename: Carlo
authors.initials: C
authors.lastname: Cattani
authors.forename: Wanliang
authors.initials: W
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D001000:Ants; D005075:Biological Evolution; D007360:Intelligence; D008954:Models, Biological