Strategy evaluation using system dynamics and multi-objective optimization for an internal supply chain
Pages 2033 - 2044
Abstract
System dynamics, which is an approach built on information feedbacks and delays in the model in order to understand the dynamical behavior of a system, has successfully been implemented for supply chain management problems for many years. However, research within in multi-objective optimization of supply chain problems modelled through system dynamics has been scares. Supply chain decision making is much more complex than treating it as a single objective optimization problem due to the fact that supply chains are subjected to the multiple performance measures when optimizing its process. This paper presents an industrial application study utilizing the simulation based optimization framework by combining system dynamics simulation and multi-objective optimization. The industrial study depicts a conceptual system dynamics model for internal logistics system with the aim to evaluate the effects of different material flow control strategies by minimizing total system work-on-process as wells as total delivery delay.
References
[1]
Angerhofer, B.J., Angelides, M.C. 2000. "System Dynamics Modelling In Supply Chain Management: Research Review." In Proceedings of the 2000 Winter Simulation Conference. 342--351, Edited by J.A. Joines, R.B. Barton, K. Kang, P.A. Fishwick, 342--351, Piscataway, New Jersey: IEEE.
[2]
Aslam, T. 2013. "Analysis Of Manufacturing Supply Chains Using System Dynamics And Multi-Objective Optimization." PhD Dissertation, University of Skövde, Skövde, Sweden.
[3]
Aslam, T., Hedenstierna, P., Ng, A.H.C., Wang, L. 2011. "Multi-Objective Optimisation in Manufacturing Supply Chain Systems Design: A Comprehensive Survey and New Directions." In Multi-objective Evolutionary Optimisation for Product Design and Manufacturing, Edited by Wang, L., Ng, A.H.C., Deb, K. Springer London. 35--70.
[4]
Better, M., Glover, F., Kochenberger, G., Wang, H. 2008. "Simulation Optimization: Application In Risk Management." International Journal Information Technology and Decision Making 07: 571--587.
[5]
Brailsford, S.C., Hilton, N.A. 2001. "A Comparison Of Discrete Event Simulation And System Dynamics For Modelling Health Care Systems." In Planning for the Future: Health Service Quality and Emergency Accessibility, Edited by Riley, J. Glasgow Caledonian University.
[6]
Brito, T.B., Trevisan, E.F.C., Botter, R.C. 2011. "A Conceptual Comparison Between Discrete And Continuous Simulation To Motivate The Hybrid Simulation Methodology." In Proceedings of the 2011Winter Simulation Conference, Edited by S. Jain, R.R. Creasey, J. Himmelspach, K.P. White, and M. Fu. 3915--3927, Piscataway, New Jersey: IEEE.
[7]
Campuzano, F., Mula, J. 2011. "Supply Chain Simulation: A System Dynamics Approach for Improving Performance". Springer. London.
[8]
Deb, K., Sindhya, K. 2008. "Deciphering Innovative Principles For Optimal Electric Brushless D.C. Permanent Magnet Motor Design." Presented at the IEEE Congress on Evolutionary Computation. 2283--2290.
[9]
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T. 2002. "A Fast And Elitist Multiobjective Genetic Algorithm: NSGA-II." IEEE Transactions on Evolutionary Computation 6:182--197.
[10]
Dudas, C., Hedenstierna, P., Ng, A.H.C. 2011. "Simulation-Based Innovization For Manufacturing Systems Analysis Using Data Mining And Visual Analytics." In Proceedings of 4th International Swedish Production Symposium, Lund, Sweden.
[11]
Duggan, J. 2008. "Using System Dynamics And Multiple Objective Optimization To Support Policy Analysis For Complex Systems." In Complex Decision Making. Edited by Qudrat-Ullah, H., Spector, J.M. and Davidsen P.I. Springer. New York. 59--81.
[12]
Forrester, J.W. 1961. Industrial Dynamics. Pegasus Communications.
[13]
Georgiadis, P., Vlachos, D., Iakovou, E. 2005. "A System Dynamics Modeling Framework For The Strategic Supply Chain Management Of Food Chains." Journal of Food Engineering, 70: 351--364.
[14]
Gottschalk, P. 1986. "System Dynamics And Multiple-Criteria Decision Making." System Dynamic Review 2: 67--67.
[15]
Hedenstierna, P. 2010. "Applying Multi-Objective Optimisation To Dynamic Supply Chain Models." Conradi Research Review 6: 19--31.
[16]
Hong, L.J. 2005. "Discrete Optimization Via Simulation Using Coordinate Search." In Proceedings of the 2005 Winter Simulation Conference, Edited by M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines. 803--810, Piscataway, New Jersey: IEEE.
[17]
Hopp, W.J., Spearman, M.L. 2011. Factory Physics. Waveland Press, Long Grove, Ill.
[18]
Morecroft, J. 2007. Strategic Modelling and Business Dynamics: A Feedback Systems Approach. John Wiley & Sons.
[19]
Ng, A.H.C., Dudas, C., Nießen, J., Deb, K. 2011. "Simulation-Based Innovization Using Data Mining for Production Systems Analysis." In Multi-objective Evolutionary Optimization for Product Design and Manufacturing, Edited by Wang, L., Ng, A.H.C., Deb, K. Springer. London. 401--429.
[20]
Ólafsson, S., Kim, J. 2002. "Simulation Optimization." In Proceedings of the 2002 Winter Simulation Conference, 79--84.
[21]
Sterman, J. 2000. Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin/McGraw-Hill c2000.
[22]
Sweetser, A. 1999. "A Comparison Of System Dynamics (SD) And Discrete Event Simulation (DES)." In: 17th International Conference of the System Dynamics Society, 20--23.
[23]
Tako, A.A., Robinson, S. 2009. "Comparing Model Development In Discrete Event Simulation And System Dynamics." In: Proceedings of the 2009 Winter Simulation Conference, 979--991, Piscataway, New Jersey: IEEE.
[24]
Towill, D.R., Del Vecchio, A. 1994. "The Application Of Filter Theory To The Study Of Supply Chain Dynamics." Production Planning & Control 5: 82--96.
- Strategy evaluation using system dynamics and multi-objective optimization for an internal supply chain
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December 2015
4051 pages
ISBN:9781467397414
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Published: 06 December 2015
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