Managing information complexity of supply chains via
agent-based genetic programming
K. Taniguchi, and T. Terano. International Journal of Electronic Business, 3 (3/4):
216--224(June 2005)
Abstract
This paper proposes agent-based formulation of a
supply chain management (SCM) system for manufacturing
firms. We model each firm as a decision-making 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 has shown good performance
against the dynamic environmental changes.
Address: Graduate School of Systems Management,
University of Tsukuba, Otsuka 3-29-1, Bunkyo-ku, Tokyo
112 0012, Japan. ' Graduate School of Systems
Management, University of Tsukuba, Otsuka 3-29-1,
Bunkyo-ku, Tokyo 112 0012, Japan
taniguti@gssm.otsuka.tsukuba.ac.jp,
terano@gssm.otsuka.tsukuba.ac.jp
%0 Journal Article
%1 oai:inderscience.com:7267
%A Taniguchi, Ken
%A Terano, Takao
%D 2005
%I Inderscience Publishers
%J International Journal of Electronic Business
%K DAI, SCM, agent-based agents, algorithms, architecture, artificial blackboard business chain complexity, decision distributed e-business, electronic entropy, firms, genetic information intelligence, inventory, making management, manufacturing multi-agent programming, purchasing, sales, simulation, supply systems,
%N 3/4
%P 216--224
%T Managing information complexity of supply chains via
agent-based genetic programming
%U http://www.inderscience.com/link.php?id=7267
%V 3
%X This paper proposes agent-based formulation of a
supply chain management (SCM) system for manufacturing
firms. We model each firm as a decision-making 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 has shown good performance
against the dynamic environmental changes.
@article{oai:inderscience.com:7267,
abstract = {This paper proposes agent-based formulation of a
supply chain management (SCM) system for manufacturing
firms. We model each firm as a decision-making 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 has shown good performance
against the dynamic environmental changes.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Taniguchi, Ken and Terano, Takao},
bibsource = {OAI-PMH server at www.inderscience.com},
biburl = {https://www.bibsonomy.org/bibtex/2aca182c471707313be0de5cba02ec536/brazovayeye},
interhash = {303562132cc7e35603033dd470b1ecb2},
intrahash = {aca182c471707313be0de5cba02ec536},
issn = {1741-5063},
journal = {International Journal of Electronic Business},
keywords = {DAI, SCM, agent-based agents, algorithms, architecture, artificial blackboard business chain complexity, decision distributed e-business, electronic entropy, firms, genetic information intelligence, inventory, making management, manufacturing multi-agent programming, purchasing, sales, simulation, supply systems,},
language = {eng},
month = {June~30},
notes = {Address: Graduate School of Systems Management,
University of Tsukuba, Otsuka 3-29-1, Bunkyo-ku, Tokyo
112 0012, Japan. ' Graduate School of Systems
Management, University of Tsukuba, Otsuka 3-29-1,
Bunkyo-ku, Tokyo 112 0012, Japan
taniguti@gssm.otsuka.tsukuba.ac.jp,
terano@gssm.otsuka.tsukuba.ac.jp},
number = {3/4},
oai = {oai:inderscience.com:7267},
pages = {216--224},
publisher = {Inderscience Publishers},
relation = {ISSN online: 1741-5063 ISSN print: 1470-6067 DOI:
10.1504/05.7267},
rights = {Inderscience Copyright},
source = {IJEB (2005), Vol 3 Issue 3/4, pp 216 - 224},
timestamp = {2008-06-19T17:52:50.000+0200},
title = {Managing information complexity of supply chains via
agent-based genetic programming},
url = {http://www.inderscience.com/link.php?id=7267},
volume = 3,
year = 2005
}