Fuzzy adaptive agent for supply chain management

Recent technological advances in electronic commerce have fuelled the need for designing effective strategies for supply chain management. These strategies are essential in guiding various activities within a supply chain such as component acquisition, inventory management, customer orders bidding, scheduling for production, and delivery. Among these activities, planning of raw material acquisition for inventory and bidding for customer orders can be extremely complex since such activities are required to deal with external entities such as suppliers and customers. Specifically, in the context of the manufacturing industry, acquiring raw materials for maintaining a flexible yet adequate inventory level is a complex issue due to the potential fluctuation in suppliers' production capacity and market demand. Designing an effective strategy for bidding customer orders is also an intricate problem due to the intense competition in fast changing market environments. In this paper, we describe the strategies of a supply chain management agent which adaptively adjusts its target inventory level and customer order bidding price based on fuzzy logic reasoning. The agent has competed in the 2006 Trading Agent Competition for Supply Chain Management and has achieved good results.

[1]  Michael J. Shaw,et al.  Simulation of Order Fulfillment in Divergent Assembly Supply Chains , 1998, J. Artif. Soc. Soc. Simul..

[2]  Peter R. Wurman,et al.  PackaTAC: a conservative trading agent , 2004, SECO.

[3]  Jason Miller,et al.  Controlling a supply chain agent using value-based decomposition , 2006, EC '06.

[4]  Keith S. Decker,et al.  Coordinated hospital patient scheduling , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[5]  Doina Precup,et al.  Redagent: winner of TAC SCM 2003 , 2004, SECO.

[6]  Thomas Wagner,et al.  TÆMS agents: enabling dynamic distributed supply chain management , 2003, Electron. Commer. Res. Appl..

[7]  Pericles A. Mitkas,et al.  A Robust Agent Design for Dynamic SCM Environments , 2006, SETN.

[8]  Christopher C. Yang,et al.  Applying Multi Agent Technology to Supply Chain Management , 2000, J. Electron. Commer. Res..

[9]  Rajagopalan Srinivasan,et al.  Agent-based supply chain management—2: a refinery application , 2002 .

[10]  Fu-Ren Lin,et al.  Integrating multi-agent negotiation to resolve constraints in fulfilling supply chain orders , 2006, Electron. Commer. Res. Appl..

[11]  Susumu Kurokawa,et al.  Modeling of supply chain: a multi-agent approach , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[12]  Nicholas R. Jennings,et al.  SouthamptonTAC: An adaptive autonomous trading agent , 2003, TOIT.

[13]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[14]  Jayashankar M. Swaminathan,et al.  Modeling Supply Chain Dynamics: A Multiagent Approach , 1998 .

[15]  Yain-Whar Si,et al.  Fuzzy Adaptive Agent for Supply Chain Management , 2006, 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

[16]  Scott Buffett.  A Markov Model for Inventory Level Optimization in Supply-Chain Management , 2005, Canadian Conference on AI.

[17]  I. Karimi,et al.  Agent-based supply chain management—1: framework , 2002 .

[18]  N. Gunasekaran,et al.  Optimizing supply chain management using fuzzy approach , 2006 .

[19]  Michael P. Wellman,et al.  The 2001 trading agent competition , 2002, Electron. Mark..

[20]  David P. Stone.  An Autonomous Agent for Supply Chain Management , 2007 .

[21]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[22]  Arun Kumar,et al.  An agent-based framework for collaborative negotiation in the global manufacturing supply chain network , 2006 .

[23]  Peter Stone,et al.  Bidding for customer orders in TAC SCM , 2004, AAMAS'04.

[24]  Huaiqing Wang,et al.  On-demand e-supply chain integration: A multi-agent constraint-based approach , 2008, Expert Syst. Appl..

[25]  Loris Penserini,et al.  Social-oriented engineering of intelligent software , 2007, Web Intell. Agent Syst..

[26]  Shyh-ming Lin,et al.  Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems , 2006, J. Artif. Soc. Soc. Simul..

[27]  F. Bodendorf,et al.  Agent-Based Supply Chain Event Management — Concept and Assessment , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[28]  Radivoj Petrovic,et al.  Supply chain modelling using fuzzy sets , 1999 .

[29]  Michael Carl Tschantz,et al.  Botticelli: a supply chain management agent designed to optimize under uncertainty , 2004, SECO.

[30]  Marlon Dumas,et al.  Strategies in supply chain management for the Trading Agent Competition , 2007, Electron. Commer. Res. Appl..

[31]  Robert de Souza,et al.  Multi-agent enabled modeling and simulation towards collaborative inventory management in supply chains , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[32]  Nicholas R. Jennings,et al.  Designing and Evaluating an Adaptive Trading Agent for Supply Chain Management , 2005, AMEC@AAMAS/TADA@IJCAI.

[33]  Darnes Vilariño Ayala,et al.  Tiancalli06: An Agent for the Supply Chain Management Game 2006 , 2006, 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06).