%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 }