Managing Information Complexity in a Supply Chain Model by Agent-Based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Taniguchi:2001:CEF,

• author = "Ken Taniguchi and Setsuya Kurahashi and Takao Terano",
• title = "Managing Information Complexity in a Supply Chain Model by Agent-Based Genetic Programming",
• booktitle = "7th International Conference of Society of Computational Economics",
• year = "2001",
• address = "Yale",
• month = "28-29 " # jun,
• organisation = "Society for Computational Economics",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://ideas.repec.org/p/sce/scecf1/238.html",
• URL = "http://econpapers.repec.org/paper/scescecf1/238.htm",
• abstract = "We propose agent-based formulation of a Supply Chain Management (SCM) system for manufacturing firms. We model each firm as an intelligent agent, which communicates each other through the blackboard architecture in distributed artificial intelligence. To overcome the issues of conventional SCM systems, we employ the concept of information entropy, which represents the complexity of the purchase, sales, and inventory activities of each firm. Based on the idea, we implement an agent-based simulator to learn `good' decisions via genetic programming in a logic programming environment. From intensive experiments, our simulator have shown good performance against the dynamic environmental changes.",
• notes = "CEF 2001 number 238. See also \cite{taniguchi:2001:micscmagp}",

}

Genetic Programming entries for Ken Taniguchi Setsuya Kurahashi Takao Terano

Citations