Integrated methodological frameworks for modeling agent-based advanced supply chain planning systems: A systematic literature review

Journal of Industrial Engineering and Management

Volumn 4, Issue 4, 2011, Pages 624-668

  Santa Eulalia, Luis Antonio ^a   Halladjian, Georgina ^a   D'Amours, Sophie ^b   Frayret, Jean Marc ^c  

^a Tel e University of Quebec   (Canada)

^b UNIVERSITÉ LAVAL   (Canada)

^c ÉCOLE POLYTECHNIQUE DE MONTRÉAL   (Canada)

Author keywords

Advanced supply chain planning systems; Agent based modelling and simulation; Methodological frameworks; Supply chain management

Indexed keywords

INDUSTRIAL APPLICATIONS; SUPPLY CHAIN MANAGEMENT;

AGENT BASED; AGENT SOCIETY; AGENT-BASED MODELLING; DESIGN/METHODOLOGY/APPROACH; INNOVATIVE RESEARCH; INTEGRATED FRAMEWORKS; LITERATURE SEARCH; METHODOLOGICAL ASPECTS; METHODOLOGICAL FRAMEWORKS; MODELLING AND SIMULATIONS; RESEARCH LIMITATIONS; SCIENTIFIC DATABASE; STATE-OF-THE-ART REVIEWS; SUPPLY CHAIN PLANNING; SYSTEMATIC LITERATURE REVIEW;

RESEARCH;

EID: 84930477884     PISSN: 20138423     EISSN: 20130953     Source Type: Journal    
DOI: 10.3926/jiem.326     Document Type: Review

References (111)

1. Amouzegar, M., & Moshirvaziri, K. (2006). A simulation framework for networked queue models: Analysis of queue bounds in a G/G/c supply chain. Journal of Applied Mathematics and Decision Sciences, 2006, 1-13. http://dx.doi.org/10.1155/JAMDS/2006/87514
2. Andreev, M., Rzevski, J., Skobelev, P., Shveykin, P., Tsarev, A., & Tugashev, A. (2007). Adaptive Planning for Supply Chain Networks. Proceedings of the 3rd International Conference on Industrial Applications of Holonic and Multi-Agent Systems, Regensburg, Germany.
3. Andrews, J., Benisch, M., Sardinha, A., & Sadeh, N. (2007). What differentiates a winning agent: An information gain based analysis of TAC-SCM. Proceedings of the Trading Agent Design and Analysis Workshop, Vancouver, Canada.
4. Baumgaertel, H., & John, U. (2003). Combining agent-based supply net simulation and constraint technology for highly efficient simulation of supply networks using APS systems. Proceedings of the 2003 Winter Simulation Conference, New Orleans, USA.
5. Beaudoin, D., Lebel, L., & Frayret, J. (2007). Tactical supply chain planning in the forest products industry through optimization and scenario-based analysis. Canadian Journal of Forest Research, 37, 128-140. http://dx.doi.org/10.1139/x06-223
6. Becheikh, N. (2005). La revue systématique de littérature: Utilité et méthode pour les sciences de l'administration. Proceedings of the Chaire FCRSS/IRSC sur le transfer de connaissances et l'innovaiton, Québec, Canada.
7. Benisch, M., Sardinha, A., Andrews, J., Ravichandran, R., & Sadeh, N. (2009). CMieux: Adaptive strategies for competitive supply chain trading. SIGecom Exch., 6(1), 1-10. http://dx.doi.org/10.1145/1150735.1150737
8. Biwer, A.G., Griffith, S., & Cooney, C. (2005). Uncertainty analysis of penicillin V production using Monte Carlo simulation. Biotechnology and Bioengineering, 90(2), 167-179. http://dx.doi.org/10.1002/bit.20359
9. Brugali, D., & Sycara, K. (2000). Towards agent oriented application frameworks. ACM Computing Surveys, 32(1), 21-26. http://dx.doi.org/10.1145/351936.351957
10. Bussmann, S., Jennings, N., & Wooldridge, M. (2004). Multi-agent systems for manufacturing control: A design methodology. Berlin: Springer.
11. Carvalho, R., & Custodio, L. (2005). A multiagent systems approach for managing supply-chain problems: A learning perspective. Proceedings of the IEEE International Conference on Integration of Knowledge Intensive Multi-agent, Systems, Boston, USA. http://dx.doi.org/10.1109/KIMAS.2005.1427124
12. Cavalieri, S.C., Cesarotti, V., & Introna, V. (2003). A multiagent model for coordinated distribution chain planning. Journal of Organizational Computing and Electronic Commerce, 13(3-4), 267-287. http://dx.doi.org/10.1080/10919392.2003.9681164
13. Chan, H.K., & Chan, F.T.S. (2010). Comparative study of adaptability and flexibility in distributed manufacturing supply chains. Decision Support Systems, 48(2), 331-341. http://dx.doi.org/10.1016/j.dss.2009.09.001
14. Chatfield, D.C., Harrison, T.P., & Hayya, J.C. (2006). SISCO: An object-oriented supply chain simulation system. Decision Support System, 42, 422-434. http://dx.doi.org/10.1016/j.dss.2005.02.002
15. Chatfield, D.C., Hayya, J.C., & Harrison. T.P. (2007). A multi-formalism architecture for agent-based, order-centric supply chain simulation. Simulation Modelling Practice and Theory, 15, 153-174. http://dx.doi.org/10.1016/j.simpat.2006.09.018
16. Chen, Y.M., & Wei, C.W. (2007). Multi-agent-oriented approach to supply chain planning and scheduling in make-to-order manufacturing. International Journal of Electronic Business, 5(4), 427-454. http://dx.doi.org/10.1504/IJEB.2007.014787
17. Chen, M., Yang, T., & Yen C. (2007). Investigating the value of information sharing in multi-echelon supply chains. Quality and Quantity, 41(3), 497-511. http://dx.doi.org/10.1007/s11135-007-9086-2
18. Chwif, L., Barretto, M.R.P., & Saliby, E. (2002). Supply chain analysis: Spreadsheet or simulation?. Proceedings of the 2002 Winter Simulation Conference, San Diego, USA.
19. Cid-Yanez, F. Frayret, J.M., & Léger, F. (2009). Evaluation of push and pull strategies in lumber production: An agent-based approach. International Journal of Production Research, 47(22), 6295-6319.
20. Dam, K., & Winikoff, M. (2004). Comparing agent-oriented methodologies. Agent-Oriented Information Systems. In P. Giorgini, B. Henderson-Sellers, & M. Winikoff (Ed.), Lecture Notes in Computer Science (pp. 78-93). Berlin: Springer-Verlag.
21. DoD (1998). Department of Defense (DoD), Modeling and Simulation (M&S) Glossary, DOD 5000.59-M, January 1998.
22. Dudek, G., & Stadtler, G. (2005). Negotiation-based collaborative planning between supply chains partners. European Journal of Operational Research, 163(3), 668-687. http://dx.doi.org/10.1016/j.ejor.2004.01.014
23. Egri, P., & Vancza, J. (2005). Cooperative planning in the supply network - a multi-agent organization model. Proceedings of the 4th International Central and Eastern European Conference on Multi-Agent Systems, Budapest, Hungary.
24. Emerson, D., & Piramuthu, S. (2004). Agent-based framework for dynamic supply chain configuration. Proceedings of the 37th Hawaii International Conference on System Sciences, Hawaii, USA. http://dx.doi.org/10.1109/HICSS.2004.1265407
25. Escalas, J. (2004). Imagine yourself in the product. Journal of Advertising, 33(2), 37-48.
26. Feng, S.C., Helaakoski, H., Jurrens, K., & Kipinä, J. (2007). Software agents-enabled systems coalition for integrated manufacturing processes and supply chain management. International Journal of Manufacturing Technology and Management, 11(2), 157-173. http://dx.doi.org/10.1504/IJMTM.2007.013183
27. Forget, P., D'Amours, S., Frayret, J.M., & Gaudreault, J. (2008). Study of the performance of multi-behaviour agents for supply chain planning. Computers in Industry, 60(9), 698-708. http://dx.doi.org/10.1016/j.compind.2009.05.005
28. Fox, M., Barbuceanu, M., & Teigen, R. (2000). Agent-oriented supply-chain management. International Journal of Flexible Manufacturing Systems, 12(2/3), 165-188. http://dx.doi.org/10.1023/A:1008195614074
29. Fox, M., Barbuceanu, M., Gani, M., & Beck, C. (1993). The integrated supply chain management system. Internal Report - Department of Industrial Engineering, University of Toronto, Canada. http://www.eil.utoronto.ca/iscm-descr.html- Accessed October 2006.
30. Frayret, J.M., D'Amours, S., Rousseau, A., Harvey, S., & Gaudreault, J. (2007). Agent-based supply-chain planning in the forest products industry. International Journal of Flexible Manufacturing Systems, 19(4), 358-391. http://dx.doi.org/10.1007/s10696-008-9034-z
31. Galland, S. (2001). Approche multi-agents pour la conception et la construction d'un environnement de simulation en vue de l'évaluation des performances des ateliers multi-sites, Ph.D. Dissertation, École Nationale Supérieure des Mines et Université Jean Monnet, France.
32. Galland, S., Grimaud, F., Beaune, P., & Campagne J. (2003). MAMA-S: An introduction to a methodological approach for the simulation of distributed industrial systems. International Journal of Production Economics, 85, 11-31. http://dx.doi.org/10.1016/S09255273(03)00083-5
33. Ganga, G.M.D. (2010). Proposta de um modelo de simulação baseado em lógica fuzzy e no SCOR para predizer o desempenho da empresa-foco em cadeias de suprimentos, Ph.D. Dissertation, Federal University of Sao Carlos, Brazil.
34. Gaudreault J., Forget, P., Frayret, J.M., Rousseau, A., & D'Amours, S. (2009). Distributed operations planning in the lumber supply chain: Models and coordination. CIRRELT Working Paper CIRRELT-2009-07, http://www.cirrelt.ca- Accessed December 2009.
35. Giorgini, P., Kolp, M., Mylopoulos, J., & Pistore, M. (2003). The Tropos methodology: An overview. In F. Bergenti, M.P. Gleizes, & F. Zambonelli (Ed.), Methodologies and Software Engineering for Agent Systems. New York: Kluwer Academic Publishing.
36. Gjerdrum, J., Shah, N., & Papageorgiou, L.G. (2001). A combined optimization and agent-based approach to supply chain modelling and performance assessment. Production Planning and Control, 12, 81-88. http://dx.doi.org/10.1080/09537280150204013
37. Govindu, R., & Chinnam, R. (2010). A software agent-component based framework for multi-agent supply chain modelling and simulation. International Journal of Modelling and Simulation, 30(2), 155-171. http://dx.doi.org/10.2316/Journal.205.2010.2.205-4931
38. Iglesias, C., González, J., & Velasco, J. (1998). Analysis and design of multiagent systems using MAS-CommonKADS. In M.P. Singh, A. Rao, & M.J. Wooldridge, Lecture Notes in Computer Science (pp. 313-327). Berlin: Springer Verlag.
39. Ivanov, D.A., Kaeschel, J., & Sokolov, B. (2007a). Integrated modelling of agile enterprise networks. International Journal of Agile Systems and Management, 2(1), 23-49.
40. Ivanov, D.A. (2009). Structure dynamics control-based framework for adaptive reconfiguration of collaborative enterprise networks. International Journal of Manufacturing Technology and Management, 17(1/2), 23-41. http://dx.doi.org/10.1504/IJMTM.2009.023777
41. Ivanov, D.A., Sokolov, B., & Kaeschel, J. (2010). A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations. European Journal of Operational Research, 200(2), 409-420. http://dx.doi.org/10.1016/j.ejor.2009.01.002
42. Ivanov, D.A., Arkhipov, A.V., & Sokolov, B.V. (2007b). Intelligent planning and control of manufacturing supply chains in virtual enterprises. International Journal of Manufacturing Technology and Management, 11(2), 209-227. http://dx.doi.org/10.1504/IJMTM.2007.013192
43. Jankowska, A., Kurbel, K., & Schreber, D. (2007). An architecture for agent-based mobile supply chain event management. International Journal of Mobile Communications, 5(3), 243-258. http://dx.doi.org/10.1504/IJMC.2007.012393
44. Jarras, I., & Chaib-draa, B. (2002). Aperçu sur les systèmes multiagents. CIRANO - Centre Universitaire de Recherche en Analyse des Organisations. http://www.cirano.qc.ca- Accessed January 2011.
45. Jung, H., Chen, F.F., & Jeong, B. (2008). Decentralized supply chain planning framework for third party logistics partnership. Computers & Industrial Engineering, 55, 348-364. http://dx.doi.org/10.1016/j.cie.2007.12.017
46. Karageorgos, A., & Mehandjiev, N. (2004). A design complexity evaluation framework for agent-based system engineering methodologies. In A. Omicini, A. Petta, & J. Pitt, (Ed.), Lecture Notes in Computer Science: Engineering Societies in the Agents World. Berlin: Springer.
47. Karam M., Tranvouez, B., Espinasse, B., & Ferrarini, A. (2010). An Organization-oriented methodological framework for agent-based supply chain simulation. Proceedings of the 4th International Conference on Research Challenges in Information Science, Nice, France.
48. Kazemi, Z.M., Aït-Kadi, D., & Nourelfath, M.(2010). Robust production planning in a manufacturing environment with random yield: A case in sawmill production planning. European Journal of Operational Research, 201(3), 882-891. http://dx.doi.org/10.1016/j.ejor.2009.03.041
49. Kim, B., & Oh, H. (2005). The impact of decision-making sharing between supplier and manufacturer on their collaboration performance. Supply Chain Management: An International Journal, 10(3), 223-236. http://dx.doi.org/10.1108/13598540510606287
50. Kim, H.S., & Cho, J.H. (2010). Supply chain formation using agent negotiation. Decision Support Systems, 49(1), 77-90. http://dx.doi.org/10.1016/j.dss.2010.01.004
51. Kitchenham, B., Brereton, O.P., Budgen, D., Turner, M., Bailey, J., & Stephen, L. (2009). Systematic literature reviews in software engineering - A systematic literature review. Information and Software Technology, 51, 7-15. http://dx.doi.org/10.1016/j.infsof.2008.09.009
52. Kleijnen, J. (2005). Supply chain simulation tools and techniques: A survey. International Journal of Simulation & Process Modelling, 1(1/2).
53. Kwon, O., Im, G., & Lee, K. (2005). MACE-SCM: An effective supply chain decision making approach based on multi-agent and case-based reasoning. Proceedings of the 38th Annual Hawaii International Conference on System Science, Hawaii, USA. http://dx.doi.org/10.1109/HICSS.2005.396
54. Labarthe, O., Espinasse, B., Ferrarini, A., & Montreuil, B. (2007). Toward a methodological framework for agent-based modelling and simulation of supply chain in a mass customization context. Simulation Modelling Practice and Theory, 15(2), 113-136. http://dx.doi.org/10.1016/j.simpat.2006.09.014
55. Lau, R., Li, Y., Song, D., & Kwok, R. (2008). Knowledge discovery for adaptive negotiation agents in e-marketplaces. Decision Support Systems, 45(2), 310-323. http://dx.doi.org/10.1016/j.dss.2007.12.018
56. Lee, C., & Liu, A. (2002). A method for agent-based system requirements analysis. Proceedings of the IEEE Fourth International Symposium on Multimedia Software Engineering, Newport Beach, USA.
57. Lee, H., & Billington, C. (1993). Material management in decentralized supply chains. Operation Research, 41(5), 835-847. http://dx.doi.org/10.1287/opre.41.5.835
58. Lee, J., & Kim, C. (2008). Multi-agent systems applications in manufacturing systems and supply chain management: a review paper. International Journal of Production Research, 46(1), 233-265. http://dx.doi.org/10.1080/00207540701441921
59. Lee, S., & Kumara, S. (2007). Decentralized supply chain coordination through auction markets: Dynamic lot-sizing in distribution networks. International Journal of Production Research, 45(20), 4715-4733. http://dx.doi.org/10.1080/00207540600844050
60. Lemieux, S., D'Amours, S., Gaudreault, J., & Frayret, J. (2009). Agent-based simulation to anticipate impacts of tactical supply chain decision-making in the lumber industry. International Journal of Flexible Manufacturing Systems, 19(4), 358-391.
61. Lendermann, P., Gan, B.P., & McGinnis, L.F. (2001). Distributed simulation with incorporated APS procedures for high-fidelity supply chain optimization. Proceedings of the 2001 Winter Simulation Conference, Arlington, USA.
62. Lin, F., Kuo, H., & Lin, S. (2008). The enhancement of solving the distributed constraint satisfaction problem for cooperative supply chains using multi-agent systems. Decision Support Systems, 45(4), 795-810. http://dx.doi.org/10.1016/j.dss.2008.02.001
63. Lin, F., Tan, G., & Shaw, M. (1998). Modeling supply-chain networks by a multi-agent system. Proceedings of the 31st Annual Hawaii International Conference on System Sciences, Hawaii, USA.
64. Michel, F., Gouaïch, A., & Ferber, J. (2003). Weak interaction and strong interaction in agent based simulations. In D. Hales, B. Edmonds, E. Norling, & J. Rouchier (Ed.), Lecture Notes in Computer Science: Multi-Agent-based Simulation III (pp. 43-56). Berlin: Springer. http://dx.doi.org/10.1007/978-3-540-24613-8_4
65. Monostori, L., Vancza, J., & Kumara, S.R.T. (2006). Agent-based systems for manufacturing. CIRP Annals - Manufacturing Technology, 55(2), 697-720.
66. Monteiro, T., Anciaux, D., Espinasse, B., Ferrarini, A., Labarthe, O., Montreuil, B., & Roy, D. (2008). L'intérêt des agents pour la simulation de la chaîne logistique, In C. Thierry, A. Thomas, & G. Bel (Ed.), La simulation pour la gestion des chaînes logistiques. Paris: Lavoisier.
67. Monteiro, T., Roy, D., & Anciaux, D. (2007). Multi-site coordination using a multi-agent system. Computers in Industry, 58(4), 367-377. http://dx.doi.org/10.1016/j.compind.2006.07.005
68. Montreuil, B., Frayret, J.M. & D'Amours, S. (2000). A strategic framework for networked manufacturing. Computers in Industry, 42(2-3), 299-317. http://dx.doi.org/10.1016/S01663615(99)00078-0
69. Moyaux, T., Chaib-draa, B., & D'Amours, S. (2007). Information sharing as a coordination mechanism for reducing the bullwhip effect in a supply chain. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 37(3), 396-409. http://dx.doi.org/10.1109/TSMCC.2006.887014
70. Ng, W., & Piplani, R. (2003). Simulation workbench for analysing multi-echelon supply chains. Integrated Manufacturing Systems, 14(5), 449-457. http://dx.doi.org/10.1108/09576060310477852
71. Nishioka, Y. (2004). Collaborative agents for production planning and scheduling (CAPPS): A challenge to develop a new software system architecture for manufacturing management in Japan. International Journal of Production Research, 42(17), 3355-3368. http://dx.doi.org/10.1080/00207540410001695989
72. Orcun, S., Asmundsson, R., Uzsoy, R., Clement, J., Pekny, J., & Rardin, R. (2007). Supply chain optimisation and protocol environment (SCOPE) for rapid prototyping and analysis of complex supply chains. Production Planning and Control, 18, 388-406. http://dx.doi.org/10.1080/09537280701417116
73. Ouhimmou, M., D'Amours, S., Beauregard, R., Aït-Kadi, D., & Chauhand, S. (2008). Furniture supply chain tactical planning optimization using a time decomposition approach. European Journal of Operational Research, 189(3), 952-970. http://dx.doi.org/10.1016/j.ejor.2007.01.064
74. Padgham, L., & Winikoff, M. (2002). Prometheus: A pragmatic methodology for engineering intelligent agents. Proceedings of the Workshop on Agent-oriented Methodologies at OOPSLA 2002, Seattle, USA.
75. Pan, A., Leung, S.Y.S, Moon, K.L., & Yeung, K.W. (2009). Optimal reorder decision-making in the agent-based apparel supply chain. Expert Systems with Applications, 36, 8571-8581. http://dx.doi.org/10.1016/j.eswa.2008.10.081
76. Paolucci, M., Revetria, R., & Tonelli, F. (2008). An Agent-based system for sales and operations planning in manufacturing supply chains. WSEAS Transactions on Business and Economics, 3(5), 103-112.
77. Parunak, H.V.D. (1998). Practical and industrial applications of agent-based systems. Environmental Research Institute of Michigan (ERIM).
78. Parunak, H.V.D., Baker, A.D., & Clark, S. (2001). The AARIA agent architecture: From manufacturing requirements to agent-based system design. Integrated Computer-Aided Engineering, 8, 45-58.
79. Parunak, V., & VanderBok, R. (1998). Modeling the extended supply network. Industrial Technology Institute.
80. Penker, M., & Wytrzens, K. (2005). Scenarios for the Austrian food chain in 2020 and its landscape impacts. Landscape and urban planning, 71(2-4), 175-189. http://dx.doi.org/10.1016/j.landurbplan.2004.03.002
81. Pfleeger, S., & Atlee, J. (2006). Software engineering: Theory and practice. New Jersey: Pearson Prentice Hall.
82. Sadeh, N.M., Hildum, D., Kjenstad, D., & Tseng, A. (1999). MASCOT: An agent-based architecture for coordinated mixed-initiative supply chain planning and scheduling. Proceedings of the Agents' 99 Workshop Agent-based Decision-Support for Managing the Interned-Enabled Supply-Chain, Seattle, USA.
83. Samuelson, D. (2005). Agents of change: how agent-based modeling may transform social science. OR/MS Today, 32(1).
84. Santa-Eulalia, L.A., Frayret, J.M., & D'Amours, S. (2008). Essay on conceptual modelling, analysis and illustration of agent-based simulations for distributed supply chain planning. INFOR: Information Systems and Operational Research, 46(2), 97-116. http://dx.doi.org/10.3138/infor.46.2.97
85. Santa-Eulalia, L.A., D'Amours, S., Frayret, J.M., & Azevedo, R.C. (2009a). On supply chain modelling and simulation techniques: A literature review taxonomy. Proceedings of the XI SIMPEP Simpósio de Engenharia de Produção, Bauru, Brazil.
86. Santa-Eulalia, L.A., Aït-Kadi, D., D'Amours, S., Frayret, J.M., & Lemieux, S. (2009b). Evaluating tactical planning and control policies for a softwood lumber supply chain through agent-based simulations. Proceedings of the IESM'2009 International Conference on Industrial Engineering and System Management, Montréal, Canada.
87. Santa-Eulalia, L.A. (2009). Agent-based simulations for advanced supply chain planning: A methodological framework for requirements analysis and deployment, Ph.D. Dissertation. Faculté des Sciences et Génie, Université Laval, Canada.
88. Santa-Eulalia, L.A., D'Amours, S., & Frayret, J.M. (2010). Modelling agent-based simulations for supply chain planning: the FAMASS methodological framework. Proceedings of the 2010 IEEE International Conference on Systems, Man, and Cybernetics, Special Session on Collaborative Manufacturing and Supply Chains, Istanbul, Turkey.
89. Santa-Eulalia, L.A., Aït-Kadi, D., D'Amours, S., Frayret, J.M., & Lemieux, S. (in press). Agent-based experimental investigations about the robustness of tactical planning and control policies in a softwood lumber supply chain. Production Planning & Control.
90. Sauter, J.A., Parunak, H.V.D., & Goic, J. (1999). ANTS in the supply chain. Proceedings of the Agents' 99 Workshop Agent-based Decision-support for Managing the Interned-enabled Supply-chain, Seattle, USA.
91. Shen, W., & Norrie, D.H. (1999). Agent-based systems for intelligent manufacturing: A state-of-the-art survey. Knowledge and Information Systems, an International Journal, 1(2), 129-156.
92. Shen, W., Norrie, D.H., & Barthès, J.P. (2001). Multi-agent systems for concurrent intelligent design and manufacturing. London: Taylor & Francis.
93. Shin, H.J. (2007). Collaborative production planning in a supply-chain network with partial information sharing. International Journal of Advanced Manufacturing Technology, 34, 981-987. http://dx.doi.org/10.1007/s00170-006-0664-6
94. Si, Y., Edmond, D., Dumas, M., & Chong, C. (2007). Strategies in supply chain management for the Trading Agent Competition. Electronic Commerce Research and Applications, 6(4), 369-382. http://dx.doi.org/10.1016/j.elerap.2006.12.001
95. Silva, C.A., Sousa, J.M.C, Runker, T.A., & Sá da Costa, J.M.G. (2009). Distributed supply chain management using ant colony optimization. European Journal of Operational Research, 199, 349-358. http://dx.doi.org/10.1016/j.ejor.2008.11.021
96. Stadtler, H. (2005). Supply chain management and advanced planning - basics, overview and challenges. European Journal of Operational Research, 163, 575-588. http://dx.doi.org/10.1016/j.ejor.2004.03.001
97. Strader, T.J., Lin, F.R., & Shaw, M.J. (1998). Simulation of order fulfilment in divergent assemble supply chains. Journal of Artificial Societies and Social Simulation, 1(2), http://jasss.soc.surrey.ac.uk/1/2/5.html.
98. Swaminathan, J., Smith, S., & Sadeh, N. (1998). Modeling supply chain dynamics: A multiagent approach. Decision Sciences, 29(3), 607-632. http://dx.doi.org/10.1111/j.1540-5915.1998.tb01356.x
99. Tranvouez, E. (2001). IAD et ordonnancement: Une approache coopérative du réordonnancement par systèmes multi-agents. Ph.D. Thesis, Université de Valenciennes et du Hainaut-Cambrésis.
100. Tranvouez, E., & Ferrarini, A. (2006). MultiAgent Modelling of Cooperative Disruption Management in Supply Chains. Proceedings of the IEEE International Conference on Service System and Service Management (ICSSSM'06), Troyes, France, October 2006.
101. Tweedale, J. (2007). Innovations in multi-agent systems. Journal of Network and Computer Applications, 30, 1089-1115. http://dx.doi.org/10.1016/j.jnca.2006.04.005
102. Ulieru, M., Norrie, D., Kremer, R., & Shen, W. (2000). A multi-resolution collaborative architecture for web-centric global manufacturing. Information Sciences, 127, 3-21. http://dx.doi.org/10.1016/S0020-0255(00)00026-8
103. Van Der Vorst, J., Tromp, S., & Van Der Zee, D.J. (2005). A simulation environment for the redesign of food supply chain networks: Modeling quality controlled logistics. Proceedings of the 2005 Winter Simulation Conference, Orlando, USA. http://dx.doi.org/10.1109/WSC.2005.1574436
104. Van Der Zee, D.J., & Van Der Vorst, J. (2005). A Modeling framework for supply chain simulation: Opportunities for improved decision making. Decision Sciences, 36(1), 65-95. http://dx.doi.org/10.1111/j.1540-5915.2005.00066.x
105. Van Horne, C., & Marier, P. (2005). The Quebec Wood Supply Game: An on-line tool for knowledge management and transfer. Proceedings of the 59th Forest Products Society Annual Meeting, Québec City, Canada.
106. Venkatadri, U., & Kiralp, R. (2007, May). DSOPP: An intelligent platform for distributed simulation of order promising protocols in supply chain networks. Proceedings of the 8th IFAC International Workshop on Intelligent Manufacturing Systems, Alicante, Spain.
107. Vernadat, F. (1996). Enterprise modelling and integration: Principles and applications. London: Chapman & Hall.
108. Wood, M., & Deloach, S.A. (2000). An Overview of the multi-agent systems engineering methodology. Proceedings of the 1st International Workshop on Agent-oriented Software Engineering, Limerick, Ireland.
109. Wooldridge, M., Jennings, N., & Kinny, D. (2000). The Gaia methodology for agent-oriented analysis and design. Autonomous Agents and Multi-Agent Systems, 3, 285-312. http://dx.doi.org/10.1023/A:1010071910869
110. Wu, J., Cobzaru, M., Ulieru, M., & Norrie, D. (2000). SC-Web-CS: Supply chain web-centric systems. Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, Banff, Canada.
111. Yain-Whar, S., Edmond, D., Dumas, M., & Chong, C.U. (2007). Strategies in supply chain management for the Trading Agent Competition. Electronic Commerce Research and Applications, 6, 369-382. http://dx.doi.org/10.1016/j.elerap.2006.12.001