Managing information complexity of supply chains via agent-based genetic programming. (1st July 2005)

• Record Type: Journal Article
• Authors: Taniguchi, Ken; Terano, Takao
• Is Part Of: International journal of electronic business. Volume 3:Number 3/4(2005)
• Page Start: 216
• Page End: 224
• Publication Date: 2005-07-01
• Subjects: supply chain management -- SCM -- information entropy -- genetic programming -- information complexity -- information management -- manufacturing firms -- decision making agents -- blackboard architecture -- distributed artificial intelligence -- DAI -- purchasing -- sales -- inventory -- simulation -- agent-based systems -- multi-agent systems -- genetic algorithms -- e-business -- electronic business; Electronic commerce -- Periodicals; 658.05467805
• Languages: English
• ISSNs: 1470-6067

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.