C. Study and M. , 130 2.1. Environment modelling, p.134

C. Generale and E. , 164 REFERENCES APICS Dictionary 12th Edition, 2008.

R. H. Ballou, Business Logistics: Supply Chain Management, 5 edition, 2003.

B. Basturk and D. Karaboga, An artificial bee colony (ABC) algorithm for numeric function optimization, IEEE Swarm Intelligence Symposium, pp.687-697, 2006.

B. M. Beamon and J. M. Bermudo, A hybrid push/pull control algorithm for multi-stage, multi-line production systems, Production Planning & Control, vol.11, issue.4, pp.349-356, 2000.
DOI : 10.1080/095372800232072

E. Bonabeau, Agent-based modeling: Methods and techniques for simulating human systems, Proceedings of the National Academy of Sciences, vol.32, issue.6803, pp.7280-7287, 2002.
DOI : 10.1016/S1389-1286(00)00026-8
URL : http://www.pnas.org/content/99/suppl_3/7280.full.pdf

M. C. Bonney, Z. Zhang, M. A. Head, C. C. Tien, and R. J. Barson, Are push and pull systems really so different?, International Journal of Production Economics, vol.59, issue.1-3, pp.53-64, 1999.
DOI : 10.1016/S0925-5273(98)00094-2

A. M. Bonvik, C. E. Couch, and S. B. Gershwin, A comparison of production-line control mechanisms, International Journal of Production Research, vol.35, issue.3, pp.789-804, 1997.
DOI : 10.1080/002075497195713

A. M. Bonvik and S. B. Gershwin, Beyond Kanban: Creating and analyzing lean shop floor control policies In Manufacturing and service operations management conference proceeding Business Dictionary, 2016. What is stock position? definition and meaning, pp.46-51, 1996.

J. A. Buzacott, Queueing models of Kanban and MRP controlled production systems, Engineering Costs and Production Economics, vol.17, issue.1-4, 1989.
DOI : 10.1016/0167-188X(89)90050-5

N. Chiadamrong, T. Techalert, and A. Pichalai, Decision Support Tool for Evaluating Push and Pull Strategies in the Flow Shop with a Bottleneck Resource, Ind. Eng. Manag. Syst, vol.6, pp.83-93, 2007.

M. Christopher, Logistics: The strategic issues, 1992.

J. K. Cochran and H. A. Kaylani, Optimal design of a hybrid push/pull serial manufacturing system with multiple part types, International Journal of Production Research, vol.46, issue.4, pp.949-965, 2008.
DOI : 10.1016/S0377-2217(98)00108-8

J. R. Costanza, The quantum leap in speed-to-market, 1996.

Y. Dallery and G. Liberopoulos, Extended kanban control system: combining kanban and base stock, IIE Transactions, vol.63, issue.4, pp.369-386, 2000.
DOI : 10.1287/opre.44.1.50

M. Dorigo, V. Maniezzo, and A. Colorni, Ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.26, issue.1, pp.29-41, 1996.
DOI : 10.1109/3477.484436

T. A. Feo and M. G. Resende, A probabilistic heuristic for a computationally difficult set covering problem, Operations Research Letters, vol.8, issue.2, pp.67-71, 1989.
DOI : 10.1016/0167-6377(89)90002-3

F. Fontanili, M. Lauras, and J. Lamothe, Pour une ingénierie d'entreprise plus performante par couplage entre modélisation de processus et simulation, 2013.

J. W. Forrester, The Beginning of System Dynamics, McKinsey Q, vol.4, 1995.

J. W. Forrester, Industrial Dynamics, 1961.

E. G. Gaury, Designing pull production control systems : Customization and robustness, 2000.

E. G. Gaury, J. P. Kleijnen, and H. Pierreval, A methodology to customize pull control systems, Journal of the Operational Research Society, vol.52, issue.7, pp.789-799, 2001.
DOI : 10.1057/palgrave.jors.2601153
URL : https://hal.archives-ouvertes.fr/hal-00118204

J. Geraghty, C. Heavey, and S. B. Gershwin, A review and comparison of hybrid and pull-type production control strategies. Spectr Design and operation of manufacturing systems: the control-point policy, pp.435-457, 2000.

W. G. Gilland, A simulation study comparing performance of CONWIP and bottleneck-based release rules, Production Planning & Control, vol.36, issue.1, pp.211-219, 2002.
DOI : 10.1111/j.1937-5956.1997.tb00409.x

F. Glover and M. Laguna, Handbook of Combinatorial Optimization, Tabu Search *, pp.3261-3362, 2013.

E. M. Goldratt, Theory of constraints, 1990.

E. M. Goldratt and J. Cox, The goal: Excellence in manufacturing, 1984.

P. L. González-r, J. M. Framinan, and H. Pierreval, Token-based pull production control systems: an introductory overview, Journal of Intelligent Manufacturing, vol.176, issue.1, pp.5-22, 2011.
DOI : 10.1016/j.ejor.2005.06.053

G. A. Gordon and M. Fischer, Accounting Strategy to Improve Public Higher Education Management, J. Account. Finnance, 2011.

A. Gunasekaran, C. Patel, and R. E. Mcgaughey, A framework for supply chain performance measurement, Supply Chain Management for the 21st Century Organizational Competitiveness, pp.333-347, 2004.
DOI : 10.1016/j.ijpe.2003.08.003
URL : http://www.umassd.edu/charlton/birc/pm_scm.pdf

S. M. Gupta, Y. A. Al-turki, and R. F. Perry, Flexible kanban system, International Journal of Operations & Production Management, vol.19, issue.10, 1999.
DOI : 10.1016/0925-5273(91)90093-9

T. A. Hochreiter, A Comparative Simulation Study of Kanban, CONWIP, and MRP Manufacturing Control Systems in a flow shop (M. Sc. Dissertation), 1999.

T. J. Hodgson and D. Wang, Optimal hybrid push/pull control strategies for a parallel multistage system: Part I, International Journal of Production Research, vol.26, issue.6, pp.1279-1287, 1991.
DOI : 10.1111/j.1540-5915.1975.tb00993.x

T. J. Hodgson and D. Wang, Optimal hybrid push/pull control strategies for a parallel multistage system: Part II, International Journal of Production Research, vol.29, issue.7, pp.1453-1460, 1991.
DOI : 10.1080/00207547708943149

J. H. Holland, Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence, 1975.

B. W. Hollocks, Forty years of discrete-event simulation???a personal reflection, Journal of the Operational Research Society, vol.52, issue.12, 2006.
DOI : 10.1057/palgrave.jors.2601208

M. S. Hopp and . Mcgraw-h, Factory Physics Second Edition, International Edition edition, 2009.

W. Hopp and M. Spearman, Factory Physics: Foundations of Factory, 1996.

Z. Huq and F. Huq, Embedding JIT in MRP: The case of job shops, Journal of Manufacturing Systems, vol.13, issue.3, pp.153-16410, 1994.
DOI : 10.1016/0278-6125(94)90001-9

C. Hwang, Simulated annealing: Theory and applications, Acta Appl. Math, vol.12, pp.108-111, 1988.

M. Ihme and R. Stratton, Evaluating Demand Driven MRP: a case based simulated study, 2015.

Y. Jaegler, P. Burlat, and S. Lamouri, The ConWIP Production Control System: a Literature Review, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01350666

N. R. Jennings, On agent-based software engineering, Artificial Intelligence, vol.117, issue.2, pp.277-296, 2000.
DOI : 10.1016/S0004-3702(99)00107-1

J. Jiang and S. Rim, Strategic Inventory Positioning in BOM with Multiple Parents Using ASR Lead Time, Mathematical Problems in Engineering, vol.75, issue.1, pp.1-9, 2016.
DOI : 10.1016/s0377-2217(99)00184-8
URL : http://doi.org/10.1155/2016/9328371

L. A. Johnson and D. C. Montgomery, Operations Research in Production Planning, 1974.

D. Jones, Heijunka: Leveling production, Manuf. Eng, vol.137, p.29, 2006.

Y. Khojasteh and R. Sato, Selection of a pull production control system in multi-stage production processes, International Journal of Production Research, vol.33, issue.1, pp.4363-4379, 2015.
DOI : 10.1111/j.1937-5956.2000.tb00463.x

Y. Khojasteh-ghamari, Developing a framework for performance analysis of a production process controlled by Kanban and CONWIP, Journal of Intelligent Manufacturing, vol.93, issue.94, pp.61-71, 2009.
DOI : 10.1016/j.ijpe.2004.06.003

G. E. Kimball, General principles of inventory control, pp.119-130, 1988.

J. P. Kotter, Leading Change, With a New Preface by the Author, 1 edition, Harvard Business Review Press, 2012.

D. E. Koulouriotis, A. S. Xanthopoulos, and V. D. Tourassis, Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms, International Journal of Production Research, vol.33, issue.10, pp.2887-29121000207540802603759, 1080.
DOI : 10.1016/j.ijpe.2004.06.003

L. Junior, M. , G. Filho, and M. , Variations of the kanban system: Literature review and classification, Int. J. Prod. Econ, vol.125, 2010.

M. J. Land, Cobacabana (control of balance by card-based navigation): A card-based system for job shop control, International Journal of Production Economics, vol.117, issue.1, 2009.
DOI : 10.1016/j.ijpe.2008.08.057

A. Law, Simulation Modeling and Analysis, 5 edition, 2014.

H. L. Lee, V. Padmanabhan, and S. Whang, Information Distortion in a Supply Chain: The Bullwhip Effect, Manag. Sci, vol.43, 1997.

X. Li, R. Sawhney, E. J. Arendt, and K. Ramasamy, A comparative analysis of management accounting systems' impact on lean implementation, International Journal of Technology Management, vol.57, issue.1/2/3, pp.33-48, 2012.
DOI : 10.1504/IJTM.2012.043950

Z. Li, Design and Analysis of Robust Kanban System in an Uncertain Environment, 2013.

S. A. Melnyk and C. J. Piper, Implementation of Material Requirements Planning: Safety Lead Times, International Journal of Operations & Production Management, vol.2, issue.1, pp.52-61, 1981.
DOI : 10.1287/mnsc.14.8.B449

S. A. Melnyk, A. Rodrigues, and G. L. Ragatz, Using Simulation to Investigate Supply Chain Disruptions, Supply Chain Risk, International Series in Operations Research & Management Science, pp.103-122, 2009.
DOI : 10.1007/978-0-387-79934-6_7

R. Miclo, F. Fontanili, M. Lauras, J. Lamothe, and B. Milian, MRP vs. demand-driven MRP: Towards an objective comparison, 2015 International Conference on Industrial Engineering and Systems Management (IESM), pp.1072-1080, 2015.
DOI : 10.1109/IESM.2015.7380288
URL : https://hal.archives-ouvertes.fr/hal-01611000

R. Miclo, F. Fontanili, G. Marquès, P. Bomert, and M. Lauras, RTLS-based Process Mining: Towards an automatic process diagnosis in healthcare, IEEE International Conference on Automation Science and Engineering (CASE), pp.2015-1397, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01609202

R. Miclo, M. Lauras, F. Fontanili, J. Lamothe, P. Bornert et al., Working Capital Improvement through Value Stream Mapping Costing and Discrete-Event Simulation, Proc. 5th Int. Conf. Inf. Syst. Logist. Supply Chain Connect. WORLDS ILS 2014, 2014.

N. Mladenovi? and P. Hansen, Variable neighborhood search, Computers & Operations Research, vol.24, issue.11, pp.1097-1100, 1997.
DOI : 10.1016/S0305-0548(97)00031-2

T. Ohno, Toyota Production System, 1988.
DOI : 10.1007/978-3-642-27922-5_14

J. Olhager, B. Östlund, and J. A. Orlicky, An integrated push-pull manufacturing strategy, European Journal of Operational Research, vol.45, issue.2-3, pp.135-142, 1975.
DOI : 10.1016/0377-2217(90)90180-J

C. Ptak and C. Smith, Orlicky's Material Requirements Planning 3, 2011.

S. Rim, J. Jiang, and C. J. Lee, Strategic Inventory Positioning for MTO Manufacturing Using ASR Lead Time Logistics Operations, Supply Chain Management and Sustainability, pp.441-456, 2014.
DOI : 10.1007/978-3-319-07287-6_31

A. Rushton, P. Croucher, D. P. Baker, C. I. Transport, and L. Of, The Handbook of Logistics and Distribution Management, 2010.

B. R. Sarker and J. A. Fitzsimmons, The performance of push and pull systems: a simulation and comparative study???, International Journal of Production Research, vol.4, issue.10, pp.1715-1731, 1989.
DOI : 10.1080/00207547708943149

T. J. Schriber, D. T. Brunner, and J. S. Smith, How discrete-event simulation software works and why it matters, Simulation Conference (WSC) Proceedings of the 2012 Winter. Presented at the Simulation Conference Proceedings of the 2012 Winter, pp.1-15, 2012.
DOI : 10.1109/wsc.2012.6465274
URL : http://www.informs-sim.org/wsc12papers/includes/files/inv218.pdf

K. Sekine, One-Piece Flow: Cell Design for Transforming the Production Process, 2005.

M. M. Sepehri and N. Nahavandi, Critical WIP loops: a mechanism for material flow control in flow lines, International Journal of Production Research, vol.35, issue.12, pp.2759-2773, 2007.
DOI : 10.1080/00207549008942761

D. Sipper and R. L. Bulfin, Production: Planning, Control and Integration, International Ed edition, 1997.

G. D. Sivakumar and P. Shahabudeen, Design of multi-stage adaptive kanban system, Int. J, 2008.
DOI : 10.1007/s00170-007-1093-x

. M. Adv, N. Slack, and M. Lewis, Demand Driven Performance, Operations Strategy, vol.38, pp.321-336, 2015.

M. L. Spearman, D. L. Woodruff, and W. J. Hopp, CONWIP: a pull alternative to kanban, International Journal of Production Research, vol.28, issue.5, 1990.
DOI : 10.1080/00207549008942761

M. S. Spencer and J. F. Cox, Optimum production technology (OPT) and the theory of constraints (TOC): analysis and genealogy, International Journal of Production Research, vol.27, issue.6, pp.1495-1504, 1995.
DOI : 10.1080/00207549108948038

M. Stevenson, L. C. Hendry, and B. G. Kingsman, A review of production planning and control: the applicability of key concepts to the make-to-order industry, International Journal of Production Research, vol.22, issue.5, pp.869-89810, 1080.
DOI : 10.1016/0377-2217(93)90287-W

Y. Sugimori, K. Kusunoki, F. Cho, and S. Uchikawa, Toyota production system and Kanban system Materialization of just-in-time and respect-for-human system, International Journal of Production Research, vol.15, issue.6, pp.553-5641000207547708943149, 1080.
DOI : 10.1080/00207547708943149

R. Suri, Quick response manufacturing: A company-wide approach to lead time reduction, 1998.

K. Takahashi and N. Nakamura, Comparing reactive Kanban and reactive CONWIP, Production Planning & Control, vol.3, issue.4, 2002.
DOI : 10.1287/mnsc.39.11.1347

V. Tardif and L. Maaseidvaag, An adaptive approach to controlling kanban systems, European Journal of Operational Research, vol.132, issue.2, 2001.
DOI : 10.1016/S0377-2217(00)00119-3
URL : http://www.me.utexas.edu/~vtardif/Research/Papers/adaptive.pdf

A. A. Thompson, M. Peteraf, J. E. Gamble, and A. J. Iii, Crafting & Executing Strategy: The Quest for Competitive Advantage: Concepts and Cases, 2013.

A. Villa and T. Watanabe, Production management: Beyond the dichotomy between ???push??? and ???pull???, Computer Integrated Manufacturing Systems, vol.6, issue.1, pp.53-63, 1080.
DOI : 10.1016/0951-5240(93)90028-O

O. Wight, Manufacturing Resource Planning: MRP II: Unlocking America's Productivity Potential, 1995.