Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0098-1354(02)00150-3
Title: Agent-based supply chain management - 1: Framework
Authors: Julka, N.
Srinivasan, R. 
Karimi, I. 
Keywords: Grafcets
Software agents
Supply chain modeling
Issue Date: 15-Dec-2002
Source: Julka, N., Srinivasan, R., Karimi, I. (2002-12-15). Agent-based supply chain management - 1: Framework. Computers and Chemical Engineering 26 (12) : 1755-1769. ScholarBank@NUS Repository. https://doi.org/10.1016/S0098-1354(02)00150-3
Abstract: In the face of highly competitive markets and constant pressure to reduce lead times, enterprises today consider supply chain management to be the key area where improvements can significantly impact the bottom line. More enterprises now consider the entire supply chain structure while taking business decisions. They try to identify and manage all critical relationships both upstream and downstream in their supply chains. Some impediments to this are that the necessary information usually resides across a multitude of resources, is ever changing, and is present in multiple formats. Most supply chain decision support systems (DSSs) are specific to an enterprise and its supply chain, and cannot be easily modified to assist other similar enterprises and industries. In this two-part paper, we propose a unified framework for modeling, monitoring and management of supply chains. The first part of the paper describes the framework while the second part illustrates its application to a refinery supply chain. The framework integrates the various elements of the supply chain such as enterprises, their production processes, the associated business data and knowledge and represents them in a unified, intelligent and object-oriented fashion. Supply chain elements are classified as entities, flows and relationships. Software agents are used to emulate the entities i.e. various enterprises and their internal departments. Flows - material and information - are modeled as objects. The framework helps to analyze the business policies with respect to different situations arising in the supply chain. We illustrate the framework by means of two case studies. A DSS for petrochemical cluster management is described together with a prototype DSS for crude procurement in a refinery. © 2002 Elsevier Science Ltd. All rights reserved.
Source Title: Computers and Chemical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/66435
ISSN: 00981354
DOI: 10.1016/S0098-1354(02)00150-3
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