SCAMM-CPA: A supply chain agent-based modelling methodology that supports a collaborative planning process

Multi-agent system technologies are currently becoming a strong modelling tool for supporting the complexities present in planning supply chains. As supply chains are composed by nodes needing common agreement to fulfil their own requirements, the multi-agent system thus represents a suitable tool for modelling negotiation, mainly within a collaborative context. Nevertheless, a review of the relevant literature revealed a certain deficiency in existing agent-based modelling methodologies supporting collaborative supply chain planning. This paper has thus proposed a novel agent-based modelling methodology to cover such deficiency to make a real contribution towards supply chain agent-based modelling within a collaborative planning environment. This methodology was supported by the relevant aspects found in the literature review regarding collaborative planning within a multi-agent context (agent definition, scope, decisional level, distribution and supply chain network entities, modelling technique, interaction, coordination mechanism, advantages and disadvantages) and explicit methodologies supporting the agent-based modelling of any type of problem under consideration. By considering the corresponding literature review, the proposed new methodology synthesised existing knowledge in the field and both fulfilled and enriched each of its phases with our own modellers' knowledge. This study adopted a static view of a real automotive supply chain network so as to present a first real multi-agent-based supply chain model approach as an application of this novel modelling methodology.

[1]  Michael Winikoff,et al.  Prometheus: A Methodology for Developing Intelligent Agents , 2002, AOSE.

[2]  Jürgen Bode,et al.  Application of multiagent systems in project management , 2000 .

[3]  G. Barbarosoglu,et al.  Hierarchical design of an integrated production and 2-echelon distribution system , 1999, Eur. J. Oper. Res..

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

[5]  Pierre Massotte,et al.  Comparison of negotiation protocols in dynamic agent-based manufacturing systems , 2006 .

[6]  Josefa Mula,et al.  A collaborative knowledge management framework for supply chains: a UML-based model approach , 2008 .

[7]  Raul Poler Escoto,et al.  A conceptual model for the production and transport planning process: An application to the automobile sector , 2008, Comput. Ind..

[8]  Christoph Schneeweiss,et al.  Distributed decision making in supply chain management , 2003 .

[9]  Nicholas R. Jennings,et al.  USING REINFORCEMENT LEARNING TO COORDINATE BETTER , 2005, Comput. Intell..

[10]  Bongju Jeong,et al.  Decentralised production-distribution planning system using collaborative agents in supply chain network , 2005 .

[11]  Francisco García-Sánchez,et al.  An ontology, intelligent agent-based framework for the provision of semantic web services , 2009, Expert Syst. Appl..

[12]  François B. Vernadat,et al.  Distributed client/server architecture for CIMOSA-based enterprise components , 2004, Comput. Ind..

[13]  Andrea Omicini,et al.  SODA: Societies and Infrastructures in the Analysis and Design of Agent-Based Systems , 2000, AOSE.

[14]  Bongju Jeong,et al.  Decentralized supply chain planning framework for third party logistics partnership , 2008, Comput. Ind. Eng..

[15]  Quynh-Nhu Numi Tran,et al.  MOBMAS: A methodology for ontology-based multi-agent systems development , 2008, Inf. Softw. Technol..

[16]  Riza Cenk Erdur,et al.  SABPO: A Standards Based and Pattern Oriented Multi-agent Development Methodology , 2002, ESAW.

[17]  M. Cooper.  MESHING MULTIPLE ALLIANCES , 1997 .

[18]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[19]  Umesh Deshpande,et al.  Performance enhancement of a contract net protocol based system through instance-based learning , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[20]  James C. Spohrer,et al.  KidSim: programming agents without a programming language , 1994, CACM.

[21]  J. Hagel,et al.  Unbundling the corporation. , 1999, Harvard business review.

[22]  Arthur C. Graesser,et al.  Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents , 1996, ATAL.

[23]  Francisco-Cruz Lario,et al.  Order promising process for extended collaborative selling chain , 2008 .

[24]  Christoph Schneeweiss,et al.  Hierarchical coordination mechanisms within the supply chain , 2004, Eur. J. Oper. Res..

[25]  M. Lejeune,et al.  On characterizing the 4 C's in supply chain management , 2005 .

[26]  Marc Esteva,et al.  ISLANDER: an electronic institutions editor , 2002, AAMAS '02.

[27]  Josefa Mula,et al.  Capacity and material requirement planning modelling by comparing deterministic and fuzzy models , 2008 .

[28]  M. Caridi,et al.  Improving supply-chain collaboration by linking intelligent agents to CPFR , 2005 .

[29]  Hing Kai Chan,et al.  A new model for manufacturing supply chain networks: A multiagent approach , 2004 .

[30]  Gauthier Picard,et al.  ADELFE: A Methodology for Adaptive Multi-agent Systems Engineering , 2002, ESAW.

[31]  Vicky Manthou,et al.  Virtual e-Chain (VeC) model for supply chain collaboration , 2004 .

[32]  Gong Wang,et al.  A study on multi-agent supply chain framework based on network economy , 2008, Comput. Ind. Eng..

[33]  Bernhard Bauer,et al.  Agent UML : A formalism for specifying multiagent interaction , 2001 .

[34]  D. Lambert,et al.  Issues in Supply Chain Management , 2000 .

[35]  Toshiya Kaihara,et al.  A study on agent behaviour conducting Pareto optimality in virtual market , 2003, Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694).

[36]  Hartmut Stadtler,et al.  Negotiation-based collaborative planning between supply chains partners , 2005, Eur. J. Oper. Res..

[37]  Hendrik Van Brussel,et al.  Multi-agent coordination and control using stigmergy , 2004, Comput. Ind..

[38]  Josefa Mula,et al.  A reference model for conceptual modelling of production planning processes , 2008 .

[39]  Timothy W. Finin,et al.  A negotiation-based Multi-agent System for Supply Chain Management , 1999 .

[40]  Jorge J. Gómez-Sanz,et al.  Agent Oriented Analysis Using Message/UML , 2001, AOSE.

[41]  Ercan Öztemel,et al.  Interactions of agents in performance based supply chain management , 2009, J. Intell. Manuf..

[42]  Jordi Sabater-Mir,et al.  Evolutionary programming in SADDE , 2002, AAMAS '02.

[43]  Frédéric Grimaud,et al.  An introduction to a methodological approach for the simulation of distributed industrial systems , 2003 .

[44]  Valeria Seidita,et al.  From PASSI to Agile PASSI: tailoring a design process to meet new needs , 2004 .

[45]  Bradley Z. Hull.  A structure for supply‐chain information flows and its application to the Alaskan crude oil supply chain , 2002 .

[46]  Paul Davidsson,et al.  Agent based simulation architecture for evaluating operational policies in transshipping containers , 2006, Autonomous Agents and Multi-Agent Systems.

[47]  Jiexin Lian,et al.  A Modeling Methodology for Conflict Control in Multi-Agent Systems , 2008, Int. J. Softw. Eng. Knowl. Eng..

[48]  Vipul Jain,et al.  Managing long supply chain networks: some emerging issues and challenges , 2008 .

[49]  David Z. Zhang,et al.  Agent-based model for optimising supply-chain configurations , 2008 .

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

[51]  Scott A. DeLoach,et al.  An Overview of the Multiagent Systems Engineering Methodology , 2000, AOSE.

[52]  Jacques Ferber,et al.  Les Systèmes multi-agents: vers une intelligence collective , 1995 .

[53]  Mark S. Fox,et al.  Agent-Oriented Supply-Chain Management , 2000 .

[54]  Sergio Cavalieri,et al.  A Multiagent Model for Coordinated Distribution Chain Planning , 2003, J. Organ. Comput. Electron. Commer..

[55]  José Carlos González,et al.  Analysis and Design of multiagent systems using MAS-CommonKADS , 1998 .

[56]  J. M. Allwood *,et al.  The design of an agent for modelling supply chain network dynamics , 2005 .

[57]  Michael H. Coen,et al.  SodaBot: A Software Agent Environment and Construction System , 1994, AAAI.

[58]  Alessandro Brun,et al.  A multi-agent approach for the capacity allocation problem , 2000 .

[59]  Fausto Giunchiglia,et al.  Tropos: An Agent-Oriented Software Development Methodology , 2004, Autonomous Agents and Multi-Agent Systems.

[60]  Tadeusz Sawik,et al.  Coordinated supply chain scheduling , 2009 .

[61]  S. Goyal,et al.  Models for multi-plant coordination , 1993 .

[62]  Pericles A. Mitkas,et al.  A retraining methodology for enhancing agent intelligence , 2005, International Conference on Integration of Knowledge Intensive Multi-Agent Systems, 2005..

[63]  Margaret T. Malkoun,et al.  A Methodology for Developing Agent Based Systems for Enterprise Integration , 1996 .

[64]  Fredy Becerra Rodríguez.  Business networks and company dynamics: a theoretical approach , 2008 .

[65]  Clyde W. Holsapple,et al.  A unified model of supply chain agility : the work-design perspective , 2008 .

[66]  Craig R. Carter,et al.  Behavioral supply management: a taxonomy of judgment and decision‐making biases , 2007 .

[67]  Nikolay Mehandjiev,et al.  Agent-based optimisation of logistics and production planning , 2003 .

[68]  D. De La Fuente,et al.  Application of distributed intelligence to reduce the bullwhip effect , 2007 .

[69]  Barbara Hayes-Roth,et al.  An Architecture for Adaptive Intelligent Systems , 1995, Artif. Intell..

[70]  Marc-Philippe Huget.  An Application of Agent UML to Supply Chain Management , 2002, AOIS@AAMAS.

[71]  Christoph Schneeweiss,et al.  Distributed decision making--a unified approach , 2003, Eur. J. Oper. Res..

[72]  Y. Nishioka,et al.  Collaborative agents for production planning and scheduling (CAPPS): a challenge to develop a new software system architecture for manufacturing management in Japan , 2004 .

[73]  Josefa Mula,et al.  Collaborative forecasting in networked manufacturing enterprises , 2008 .

[74]  Frank Dignum,et al.  Role-assignment in open agent societies , 2003, AAMAS '03.

[75]  Hyacinth S. Nwana,et al.  ZEUS: A Toolkit for Building Distributed Multiagent Systems , 1999, Appl. Artif. Intell..

[76]  H. Van Dyke Parunak,et al.  Modeling Agents and Their Environment , 2002, AOSE.

[77]  Raul Poler Escoto,et al.  Modelling Collaborative Forecasting in Decentralized Supply Chain Networks with a Multiagent System , 2009, ICEIS.

[78]  Richard Y. K. Fung,et al.  A multiagent supply chain planning and coordination architecture , 2005 .