. .. Le-temps-disponible, 123 (54) Incertitudes : formule globale de la fonction objectif

. .. , 125 (66) Incertitudes : variable liée pour le temps disponible, Incertitudes : contrainte sur les machines 1

. .. Coût-de-qualification,

, Cas industriel

I. Partie and . Tactique,

.. .. Coût-de-revient-d'une-pièce,

. Rickenbacher, , 2013.

. Rickenbacher, , 2013.

. Rickenbacher, , 2013.

. .. Coût-d'industrialisation,

. Coût and . Baumers, , 2012.

. Coût-poudre-pièce-;-kopf, , 2018.

. .. Coût-poudre-pièce-;-), , 2009.

. Lindemann, , 2012.

. Ruffo, , 2006.

. .. Coût-d'achat,

. .. Coût-poudre,

.. .. Volume-minimum-de-poudre,

.. .. De-poudre,

. .. Nombre-de-plateaux,

. .. Volume-de-poudre,

. .. Coût-plateau,

. .. Coût-de-production,

. Coût-d'équipement-(kopf, , 2018.

, Coût machine pour une pièce (Hopkinson et Dickens, 2013)

. Ruffo, , 2006.

. Baumers, Coût machine pour une pièce, 2012.

. Lindemann, , 2012.

. Rickenbacher, Coût machine pour une pièce, 2013.

. Coût-opératoire-(mahadik and ;. ). Masel, , 2018.

). .. , , 2009.

. Des and . .. De-fabrication,

. Traitement and . .. De-plateaux,

. Objectif and . .. Verrous,

. Ordonnancement-en and . .. Additive, Typologie des problèmes de découpe et de placement

. .. Ordonnancement,

. .. Placement-dans-la-litterature,

E. De-l'art-:-optimisation and . .. Simulation,

. .. Les-methodes-exactes,

L. .. Heuristiques,

L. .. Metaheuristiques,

. .. Simulation, 215 4.1. Méthodes d'évaluation de la performance

. Optimisation and . .. Simulation,

. .. Definition-:-critere,

A. .. Multicritere,

. .. Methodes-d'evaluation-et-d'agregation,

M. Basees, . Le, and . .. De-synthese,

L. .. Fonction-d'evaluation,

L. .. Ordonnancement,

L. .. ,

. .. Le-principe-de-l'algorithme-genetique-developpe, 243 6.1. Sélection par loterie biaisée (wheel)

. Creation and . .. Individus,

L. .. Croisement-en-un-point, Croisement en deux points : Linear Order Crossover (LOX)

, Mutation de séquencement : permutation de deux plateaux, Mutation machine : échange de deux plateaux

. .. Critere-d'arret,

. Codage and . .. Solutions,

. Initialisation and . .. De-probabilite,

M. .. De-probabilites,

. .. Cas-d'etude,

. .. L'atelier,

R. .. De-l'algorithme-genetique,

R. .. De-l'entropie-croisee,

R. .. De-l'algorithme-genetique,

R. .. De-l'entropie-croisee,

. .. Comparaison,

. .. Conclusion,

, Une fois que cette double boucle d'entropie croisée est développée, il faut régler les différents paramètres afin de garantir sa convergence. Les paramètres d'entrée de l'entropie croisée à régler sont : ? Le nombre d

, ? Le nombre de solutions pièce / plateau créées

. Le-nombre,

, ? Le nombre de solutions plateau / OF créées

, Cette méthode a été implémentée, il est maintenant nécessaire de la tester sur un cas d'étude pour l'éprouver

P. V. Conclusion and . .. Conclusion,

. .. Niveau-strategique,

. .. Niveau-tactique,

. .. Niveau-strategique,

. .. Niveau-tactique, C. H. Glock, and M. D. Schneider, Machine scheduling in production : A content analysis, Applied Mathematical Modelling, vol.50, pp.279-299, 2017.

D. Ahn, H. Kim, and S. Lee, Fabrication direction optimization to minimize post-machining in layered manufacturing, International Journal of Machine Tool Design and Research, vol.47, pp.593-606, 2007.

B. Al-najjar, A. , and I. , Selecting the most efficient maintenance approach using fuzzy multiple criteria decision making, Int. J. Production Economics, vol.84, issue.02, pp.380-388, 2003.

I. Alberto, C. Azcárate, F. Mallor, M. , and P. M. , Optimization with simulation and multiobjective analysis in industrial decision-making: A case study, European Journal of Operational Research, vol.140, issue.2, pp.75-84, 2002.

M. H. Alrefaei and A. H. Diabat, A simulated annealing technique for multi-objective simulation optimization, Applied Mathematics and Computation, vol.215, pp.3029-3035, 2009.

,

H. I. Ansoff, Strategic Management, 1979.

A. Antomarchi, S. Durieux, and E. Duc, Scheduling in additive manufacturing, 12th International Conference on Modeling, Optimization and SIMulation, 2018.

A. Antomarchi, S. Durieux, and E. Duc, Impact de la fabrication additive sur la supply chain : Etat des lieux et diagnostics. Logistique and Management, 2019.

A. Antomarchi, R. Guillaume, S. Durieux, C. Thierry, and E. Duc, Capacity planning in additive manufacturing, 9th IFAC Conference on Manufacturing Modeling, Management, and Control, 2019.

R. Arya, P. Singh, and D. Bhati, A fuzzy based branch and bound approach for multi-objective linear fractional (MOLF) optimization problems, Journal of Computational Science, vol.24, pp.54-64, 2018.

, F2792-12a -Standard Terminology for Additive Manufacturing Technologies. Rapid Manufacturing Association, 2013.

F. Azadivar and G. Tompkins, Simulation optimization with qualitative variables and structural model changes: A genetic algorithm approach, European Journal of Operational Research, vol.113, issue.1, pp.169-182, 1999.

T. Back, D. B. Fogel, and Z. Michalewicz, Handbook of evolutionary computation, 1997.

F. Barahona, S. Bermon, and G. Oktay, Robust Capacity Planning in Semiconductor Manufacturing, Naval Research Logistics, pp.1-22, 2005.

N. Barnier and P. Brisset, Optimisation par algorithme génétique sous contraintes, 2014.

M. Baumers, P. Dickens, C. Tuck, and R. Hague, The cost of additive manufacturing: Machine productivity, economies of scale and technology-push, Technological Forecasting and Social Change, vol.102, pp.193-201, 2016.

M. Baumers, R. Wildman, A. , and I. , Combined build-time, energy consumption and cost estimation for direct metal laser sintering, 2012.

J. J. Beaman, 3D printing, additive manufacturing, and solid freeform fabrication: The technologies and applications of the past, present and future, NSF Workshop on Frontiers of Additive Manufacturing Research and Education, 2013.

R. Bellman, Dynamic Programming (Princeton), 1957.

, Planification des réapprovisionnements sous incertitudes pour les systèmes d'assemblage à plusieurs niveaux, 2014.

I. Bendato, L. Cassettari, R. Mosca, E. Williams, and M. Mosca, A stochastic methodology to evaluate the optimal multi-site investment solution for photovoltaic plants, Journal of Cleaner Production, vol.151, pp.526-536, 2017.

B. Berman, 3-D printing: The new industrial revolution, Business Horizons, vol.55, pp.155-162, 2012.

H. G. Beyer and B. Sendhoff, Robust optimization -A comprehensive survey, Computer Methods in Applied Mechanics and Engineering, vol.196, pp.3190-3218, 2007.

V. Bhasin and M. Bodla, Impact of 3D Printing on Global Supply Chains by 2020, 2014.

A. Bitar, Ordonnancement sur machines parallèles appliqué à la fabrication de semi-conducteurs : ateliers de photolithographie, 2015.

M. Bogers, R. Hadar, and A. Bilberg, Business Models for Additive Manufacturing: Exploring Digital Technologies, Consumer Roles, and Supply Chains, pp.1-59, 2015.

D. L. Bourell, J. J. Beaman, M. C. Leu, and D. W. Rosen, A brief history of additive manufacturing and the 2009 roadmap for additive manufacturing: looking back and looking ahead, US-Turkey Workshop on Rapid Technologies, pp.5-11, 2009.

D. Bouyssou, U. Gent, and P. Perny, Théorie du choix social et aide multicritére à la décision, 2005.

D. Bouyssou, La "crise de la recherche opérationnelle, Mathématique & Sciences Humaines, issue.161, pp.7-27, 2003.

P. H. Bovy, Concertation : facteur d'amélioration des projets, Revue Générale Des Routes et Des Aérodromes, (Hors série n°2, pp.92-99, 1994.

J. Brans and B. Mareschal, Promethee Methods. In International Series in Operations Research and Management Science, pp.163-186, 2005.

H. S. Byun and K. H. Lee, Determination of the optimal part orientation in layered manufacturing using a genetic algorithm, International Journal of Production Research, pp.37-41, 2005.

,

T. Campbell, C. Williams, O. Ivanova, and B. Garret, Could 3D Printing Change the World? Technologies, Potential, and Implications of Additive Manufacturing, pp.1-16, 2012.

V. Canellidis, J. Giannatsis, and V. Dedoussis, Genetic-algorithm-based multi-objective optimization of the build orientation in stereolithography, International Journal of Advanced Manufacturing Technology, pp.714-730, 2009.

H. K. Chan, J. Griffin, J. J. Lim, F. Zeng, and A. S. Chiu, The impact of 3D Printing Technology on the supply chain : Manufacturing and legal perspectives, International Journal of Production Economics, vol.205, pp.156-162, 2018.

A. Chergui, K. Hadj-hamou, and F. Vignat, Computers & Industrial Engineering Production scheduling and nesting in additive manufacturing, Computers & Industrial Engineering, vol.126, pp.292-301, 2018.

J. Claver, J. Gélinier, and D. Pitt, Gestion de flux en entreprise (Hermès-L), 1997.

M. Clerc, Une nouvelle métaheuristique pour l'optimisation difficile : la méthode des essaims particulaires, J3eA, vol.3, pp.1-16, 2003.

D. Cohen, M. Sargeant, and K. Somers, 3D printing takes shape. McKinsey Quarterly, pp.1-6, 2014.

L. Coleman and R. M. Casselman, Optimizing decisions using knowledge risk strategy, Journal of Knowledge Management, vol.20, issue.5, pp.936-958, 2016.

F. Comets and T. Meyre, Calcul stochastique et modèles de diffusions (Dunod), 2006.

T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2001.

M. J. Cotteleer, 3D opportunity: Additive manufacturing paths to perfomance, innovation, and growth, 2014.

A. Croft, Advances in production technology, vol.30, pp.39-48, 1996.

Y. Cui, Y. Cui, and T. Tang, Sequential heuristic for the two-dimensional bin-packing problem, European Journal of Operational Research, vol.240, pp.43-53, 2015.

G. Dantzig, Application of the Simplex Method to the Transportation Problem, Activity Analysis of Production and Allocation, pp.339-347, 1951.

P. De-boer, D. Kroese, S. Mannor, and R. Rubinstein, A Tutorial on the Cross-Entropy Method, Annals of Operations Research, pp.19-67, 2005.

J. W. Dean and M. Sharfman, Does decision process matter ? A study of strategic decision-making effectiveness, 1996.

K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan, A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, Proceedings of the Parallel Problem Solving from Nature VI, Conference, pp.849-858, 2000.

K. Deb, Multi-objective genetic algorithms: Problem difficulties and construction of test functions, Evolutionary Computation, pp.205-230, 1999.

K. Deb and R. B. Agrawal, Simulated Binary Crossover for Continuous Search Space, Complex Systems, 1994.

M. Defraeye, I. Nieuwenhuyse, and . Van, A branch-and-bound algorithm for shift scheduling with stochastic nonstationary demand, Computers & Operations Research, vol.65, pp.149-162, 2016.

G. Dellino, J. P. Kleijnen, and C. Meloni, Robust optimization in simulation: Taguchi and Response Surface Methodology, International Journal of Production Economics, vol.125, issue.1, pp.52-59, 2010.

D. Dentcheva, A. Prékopa, and A. Ruszczyski, Bounds for probabilistic integer programming problems, Discrete Applied Mathematics, vol.124, issue.1-3, pp.329-337, 2002.

D. Angelo, L. , D. Stefano, and P. , A neural network-based build time estimator for layer manufactured objects, International Journal of Manufacturing Technology, pp.215-224, 2011.

I. Doltsinis and Z. Kang, Robust design of structures using optimization methods, Computer Methods in Applied Mechanics and Engineering, vol.193, pp.2221-2237, 2004.

M. Dorigo and L. M. Gambardella, Ant Colony System : A Cooperative Learning Approach to the Traveling Salesman Problem, IEEE Transactions on evolutionary computation, vol.1, pp.53-66, 1997.

M. Dorigo, V. Maniezzo, and A. Colorni, Positive feedback as a search strategy, 1991.

C. Dorval, Choix des investissements. Techiques de l'ingénieur, l'entreprise Industrielle, Management, vol.2, 1981.

K. A. Dowsland, Some experiments with simulated annealing techniques for packing problems, European Journal of Operational Research, vol.68, issue.3, pp.389-399, 1993.

D. Dubois and H. Prade, Systems of linear fuzzy constraints, Fuzzy Sets and Systems, vol.3, issue.1, pp.37-48, 1980.

D. Dubois and H. Prade, La théorie des possibilités. REE, 2006.

Y. Dubromelle, T. Louati, F. Ounnar, and P. Pujo, AHP / ANP a Decision Making Service in PROSIS Model, IFAC Proceedings Volumes, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01216906

U. Dyckhoff and F. , Cutting and Packing in Production and Distribution : Typology and Bibliography, 1992.

S. Elbanna and R. Naguib, How much does performance matter in strategic decision making?, International Journal of Productivity and Performance Management, vol.58, issue.5, pp.437-459, 2009.

S. Ene, I. Küçükoglu, A. Aksoy, and N. Oztürk, A genetic algorithm for minimizing energy consumption in warehouses. Energy, vol.114, pp.973-980, 2016.

O. Engin and A. Güc, A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems, Applied Soft Computing, vol.72, pp.166-176, 2018.

T. Escobet, V. Puig, J. Quevedo, P. Palá-schönwälder, J. Romera et al., Optimal batch scheduling of a multiproduct dairy process using a combined optimization / constraint programming approach, Computers and Chemical Engineering, vol.124, pp.228-237, 2019.

,

O. Faroe, D. Pisinger, and M. Zachariasen, Guided Local Search for the Three-Dimensional Bin-Packing Problem, INFORMS Journal on Computing, vol.15, issue.3, pp.267-283, 2003.

P. C. Fishburn, A survey multiattribute/multicriterion evaluation theory, Conference on Multiple Criteria Problem Solving -Theory, 1977.

C. M. Fonseca and P. J. Fleming, Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion and Generalization. Icga, pp.416-423, 1993.

B. Francioni, F. Musso, and M. Cioppi, Decision-maker characteristics and international decisions for SMEs. Management Decision, vol.53, pp.2226-2249, 2015.

M. C. Fu, F. W. Glover, A. , and J. , Simulation optimization : A review, new developments, and applications, Winter Simulation Conference, 2005.

M. Fumey, Méthode d'évaluation des risques agrégés : application au choix des investissements de renouvellement d'installations, 2001.

W. Gao, Y. Zhang, D. Ramanujan, K. Ramani, Y. Chen et al., The status, challenges, and future of additive manufacturing in engineering, Computer-Aided Design, vol.69, pp.65-89, 2015.

N. Geng and Z. Jiang, A review on strategic capacity planning for the semiconductor manufacturing industry, International Journal of Production Research, vol.47, issue.13, pp.3639-3655, 2009.

J. Geraedts, E. Doubrovski, J. Verlinden, and M. Stellingwerff, Three views on additive manufacturing: business, research and education, Proceedings of TMCE, pp.1-15, 2012.

N. N. Glibovets and N. M. Gulayeva, A review of niching genetic algorithms for multimodal function optimization, Cybernetics and Systems Analysis, vol.49, issue.6, pp.815-820, 2013.

C. H. Glock and E. H. Grosse, Decision support models for production ramp-up: A systematic literature review, International Journal of Production Research, vol.53, issue.21, pp.6637-6651, 2015.

,

F. Glover, Tabu Search: A Tutorial, Special Issue on the Practice of Mathematical Programming (Interfaces, pp.74-97, 1990.

A. S. Gogate and S. S. Pande, Intelligent layout planning for rapid prototyping, International Journal of Production Research, vol.46, pp.5607-5631, 2008.

D. E. Goldberg, Genetic Algorithms and Walsh Functions: Part I, A Gentle Introduction, Complex Systems, vol.3, pp.129-152, 1989.

T. C. Gonçalves, J. M. Valente, and J. E. Schaller, Metaheuristics for the single machine weighted quadratic tardiness scheduling problem. Computers and Operation Research, vol.70, pp.115-126, 2016.

D. Gourc, Le management des risques en contexte projet : Quelles problématiques, Ecole d'été -Gestion scientifique du risque, 1999.

V. Griffiths, J. P. Scanlan, M. H. Eres, A. Martinez-sykora, and P. Chinchapatnam, Cost-driven build orientation and bin packing of parts in Selective Laser Melting (SLM), European Journal of Operational Research, pp.334-352, 2019.

R. Guillaume, Gestion des risques dans les chaînes logistiques : planification sous incertitude par la théorie des possibilités, 2011.

A. Guitouni and J. Martel, Tentative guidelines to help choosing an appropriate MCDA method, European Journal of Operational Research, vol.109, issue.2, pp.73-76, 1998.

E. Gurevsky, Conception de lignes de fabrication sous incertitudes: analyse de sensibilité et approche robuste, 2011.

M. Haj-rachid, C. Bloch, W. Ramdane-cherif, and P. Chatonnay, Différents opérateurs évolutionnaires de permutation : sélections, croisements et mutations, 2010.

S. Hällgren, L. Pejryd, and J. Ekengren, Additive Manufacturing and High Speed Machining -Cost Comparison of short Lead Time Manufacturing Methods. 26th CIRP Design Conference, vol.50, pp.384-389, 2016.

M. Haouari and R. Hallah, Heuristic algorithms for the two-stage hybrid flowshop problem, Operation Research Letters, vol.21, pp.43-53, 1997.

G. Harik, Finding multimodal solutions using restricted tournament selection, Proceedings of the Sixth International Conference on Genetic Algorithms, pp.24-31, 1995.

F. He, J. Yang, L. , and M. , Vehicle scheduling under stochastic trip times : An approximate dynamic programming approach, Transportation Research Part C: Emerging Technologies, vol.96, pp.144-159, 2018.

L. Henriet, Systèmes d'évaluation et de classification multicritères pour l'aide à la décision, 2000.

J. H. Holland, Adaptation in Natural and Artificial Systems, 1975.

J. Holmström, J. Partanen, J. Tuomi, and M. Walter, Rapid manufacturing in the spare parts supply chain, Journal of Manufacturing Technology Management, vol.21, pp.687-697, 2010.

,

S. Hong, D. Zhang, H. C. Lau, X. Zeng, and Y. W. Si, A hybrid heuristic algorithm for the 2D variable-sized bin packing problem, European Journal of Operational Research, vol.238, issue.1, pp.95-103, 2014.

S. J. Hood, S. Bermon, and F. Barahona, Semiconductor Manufacturing. IEEE Transactions on Semiconductor Manufacturing, vol.16, pp.273-280, 2003.

N. Hopkinson and P. Dickens, Analysis of Rapid Manufacturing -Using Layer Manufacturing Processes for Production, Mechanical Engineering Science, vol.217, pp.31-39, 2013.

J. Horn, N. Nafpliotis, and D. E. Goldberg, A Niched Pareto Genetic Algorithm for Multiobjective Optimization, Conference on Evolutionary Computation, vol.1, pp.82-87, 1994.

C. Hwang and K. Yoon, Multiple Attribute Decision Making : methods and applications a state-of-theart survey, 1981.

A. Imrani, . El, and A. Bouroumi, A fuzzy clustering-based niching approach to multimodal function optimization, Journal of Cognitive Systems Research, vol.1, pp.13-16, 2000.

D. S. Ingole, A. M. Kuthe, S. B. Thakare, and A. S. Talankar, Rapid prototyping -A technology transfer approach for development of rapid tooling, Rapid Prototyping Journal, vol.15, issue.4, pp.280-290, 2009.

S. Jakobs, On genetic algorithms for the packing of polygons, European Journal of Operational Research, vol.88, issue.1, pp.166-175, 1996.

R. J. Jansen, P. L. Cur?eu, P. A. Vermeulen, J. L. Geurts, and P. Gibcus, Information processing and strategic decision-making in small and medium-sized enterprises: The role of human and social capital in attaining decision effectiveness, International Small Business Journal, vol.31, issue.2, pp.192-216, 2013.

R. Janssen, I. Blankers, E. Moolenburgh, and B. Posthumus, TNO: The Impact of 3-D Printing on Supply Chain Management. The Hague, vol.28, p.24, 2014.

H. Z. Jia, J. Y. Fuh, A. Y. Nee, and Y. F. Zhang, Integration of genetic algorithm and Gantt chart for job shop scheduling in distributed manufacturing systems, Computers and Industrial Engineering, vol.53, pp.313-320, 2007.

S. Jukna and G. Schnitger, On the optimality of Bellman -Ford -Moore shortest path, Theoretical Computer Science, vol.628, pp.101-109, 2016.

S. Karabuk and S. D. Wu, Coordinating Strategic Capacity Planning in the Semiconductor Industry, Operations Research, pp.239-849, 2003.

S. Karakatic and V. Podgorelec, A survey of genetic algorithms for solving multi depot vehicle routing problem, Applied Soft Computing, vol.27, pp.519-532, 2015.

W. Kersten, T. Blecker, R. , and C. , Innovations and Strategies for Logistics and Supply Chains, Proceeding of the Hamburg International Conference of Logistics (HICL)-20, p.600, 2015.

S. H. Khajavi, J. Partanen, and J. Holmström, Additive manufacturing in the spare parts supply chain, Computers in Industry, vol.65, pp.50-63, 2014.

F. Kianfar and G. Mokhtari, Lot Sizing and Lead Time Quotations in Assembly Systems, Industrial Engineering, vol.16, issue.2, pp.100-113, 2009.

S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Optimization by Simulated Annealing, Science, vol.220, pp.671-680, 1983.

C. Klahn, B. Leutenecker, and M. Meboldt, Design for additive manufacturing -Supporting the substitution of components in series products, 24th CIRP Design Conference, vol.21, pp.138-143, 2014.

B. V. Elsevier,

J. Knowles, C. , and D. , The Pareto Archived Evolution Strategy : A New Baseline Algorithm for Pareto Multiobjective Optimisation, Congress on Evolutionary Computation, 1999.

R. Kopf, J. Gottwald, A. Jacob, M. Brandt, and G. Lanza, Cost-oriented planning of equipment for selective laser melting ( SLM ) in production lines, CIRP Annals -Manufacturing Technology, vol.67, pp.471-474, 2018.

R. Kopf, L. Schlesinger, S. Peters, and G. Lanza, Adjusting the Factory Planning Process when Using Immature Technologies, Procedia CIRP, vol.41, pp.1011-1016, 2016.

J. Kruth, M. C. Leu, and T. Nakagawa, Progress in Additive Manufacturing and Rapid Prototyping, CIRP Annals -Manufacturing Technology, vol.47, pp.525-540, 1998.

Y. Lambert-faivre, Risques et assurances des entreprises, 1991.

A. M. Law and W. D. Kelton, Simulation modeling and analysis, 1991.

G. Lefèvre, L'aéronautique confirme sa prédominance comme secteur vertical des applications de fabrication additive, 2017.

Q. Li, I. Kucukkoc, and D. Z. Zhang, Production planning in additive manufacturing and 3D printing, Computers and Operations Research, vol.83, pp.157-172, 2017.

X. Li and K. Zhang, Single batch processing machine scheduling with two-dimensional bin packing constraints, International Journal of Production Economics, 0196.

C. Lindemann, U. Jahnke, M. Moi, and R. Koch, Analyzing product lifecycle costs for a better understanding of cost drivers in additive manufacturing. International Solid Freeform Fabrication Symposium, vol.23, pp.177-188, 2012.

B. Liu, Theory and Practice of Uncertain Programming, 2002.

Y. Liu, Y. Fan, and B. Liu, A Workshop Scheduling and Optimization Method Based on Multi-Process Workflow Simulation, 7th IFAC Conference on Manufacturing Modelling, vol.46, pp.1738-1743, 2013.

A. Lockamy and K. Mccormack, Linking SCOR planning practices to supply chain performance, International Journal of Operations & Production Management, vol.24, pp.1192-1218, 2004.

,

C. Low, C. Hsu, and C. Su, A modified particle swarm optimization algorithm for a single-machine scheduling problem with periodic maintenance, Expert Systems With Applications, vol.37, pp.6429-6434, 2010.

A. Mahadik and D. Masel, Implementation of Additive Manufacturing Cost Estimation Tool (AMCET) Using Break-down Approach, International Conference on Flexible Automation and Intelligent Manufacturing, vol.17, pp.70-77, 2018.

O. H. Columbus and B. V. Usa:-elsevier,

J. Manners-bell and K. Lyon, The Implications of 3D P Rinting for the Global Logistics Industry, Transport Intelligence, pp.1-6, 2012.

T. Marchant, Valued Relations Aggregation with the Borda Method, Journal of Multi-Criteria Decision Analysis, issue.5, pp.127-132, 1995.

T. Marchant, Cardinality and the borda score, European Journal of Operational Research, vol.108, issue.2, pp.464-472, 1998.

C. Marmuse and X. Montaigne, , 1989.

N. Martin, B. St-onge, and J. Waab, Geographic tools for efficient decisions in watershed management. Spatial Multicriteria Decision Making and Analysis : A Geographic Information Sciences Approach, pp.309-334, 1998.

H. N. Matin, N. Salmasi, and O. Shahvari, Makespan minimization in flowshop batch processing problem with different batch compositions on machines, International Journal of Production Economics, vol.193, pp.832-844, 2017.

R. J. Mayer, M. K. Painter, and P. S. Dewitte, IDEF Family of methods for concurrent engineering and business re-engineering applications, 1994.

S. Mellor, An Implementation Framework for Additive Manufacturing, 2014.

N. Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller, Equation of state calculations by fast computing machines, Journal of Chemical Physics, pp.1087-1092, 1953.

E. Mhiri, Planification de la production à capacité finie dans un contexte à forte variabilité, application à l'industrie des semi-conducteurs, 2016.

Z. Michalewicz, C. Z. Janikow, and J. B. Krawczyk, A modified genetic algorithm for optimal control problems, Computers & Mathematics with Applications, vol.23, pp.83-94, 1992.

J. Minguella-canela, A. Muguruza, D. R. Lumbierres, J. Heredia, F. Gimeno et al., Comparison of production strategies and degree of postponement when incorporating additive manufacturing to product supply chains, Manufacturing Engineering Society International Conference, 2017.

A. Mokasdar, A Quantitative Study of the Impact of Additive Manufacturing in the Aircraft Spare Parts Supply Chain, 2012.

L. Monch, H. Balasubramanian, J. W. Fowler, and M. E. Pfund, Heuristic scheduling of jobs on parallel batch machines with incompatible job families and unequal ready times, Computers & Operations Research, vol.32, pp.2731-2750, 2005.

J. M. Moore, An n job, one machine sequencing algorithm for minimizing the number of late jobs, Management Science, pp.102-109, 1968.

Y. Mortureux, La sûreté de fonctionnement : méthodes pour maîtriser les risques, vol.33, p.17, 2001.

N. Mourgues, L'évaluation des investissements (Edition Ec), 1995.

D. Mourtzis, N. Papakostas, S. Makris, V. Xanthakis, and G. Chryssolouris, Supply chain modeling and control for producing highly customized products, CIRP Annals -Manufacturing Technology, vol.57, issue.1, pp.451-454, 2008.

M. Valenzuela and F. J. , RMADS : Development of a concurrent Rapid Manufacturing Advice System, 2009.

A. Pachauri and G. Srivastava, Automated test data generation for branch testing using genetic algorithm : An improved approach using branch ordering , memory and elitism, The Journal of Systems & Software, vol.86, issue.5, pp.1191-1208, 2013.

J. Pacheco, F. Angel-bello, and A. Alvarez, A multi-start tabu search method for a single-machine scheduling problem with periodic maintenance and sequence-dependent set-up times, Journal of Scheduling, pp.661-673, 2012.

V. M. Papadakis, Strategic Investment Decision Processes and Organizational Performance : An Empirical Examination, British Journal of Management, vol.9, pp.115-132, 1998.

C. Perkgoz, A. Azaron, H. Katagiri, K. Kato, and M. Sakawa, A multi-objective lead time control problem in multi-stage assembly systems using genetic algorithms, European Journal of Operational Research, vol.180, issue.1, pp.292-308, 2007.

I. J. Petrick and T. W. Simpson, 3D Printing Disrupts Manufacturing : How Economies of One Create New Rules of Competition, Research Technology Management, pp.12-16, 2013.

,

M. C. Piazza, A. , and S. E. , Additive Manufacturing: a Summary of the Literature Center for Economic Development, 2015.

S. Pillot, Fusion laser sélective de lit de poudres métalliques, p.7900, 2016.

P. Pujo and F. Ounnar, Pull System Control For Job Shop Via A Holonic , Isoarchic & Multicriteria Approach. IFAC Proceedings Volumes, vol.41, pp.15799-15804, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01216911

C. R. Reeves, A genetic algorithm for flowshop sequencing, Computers and Operations Research, vol.22, issue.1, pp.5-13, 1995.

P. Reeves, C. Tuck, and R. Hague, Additive Manufacturing for Mass Customization, Mass Customization: Engineering and Managing Global Operations, pp.275-289, 2011.

L. Rickenbacher, A. Spierings, and K. Wegener, An integrated cost-model for selective laser melting (SLM), Rapid Prototyping Journal, vol.19, issue.3, pp.208-214, 2013.

S. Rosat, F. Quesnel, I. Elhallaoui, and F. Soumis, Dynamic penalization of fractional directions in the integral simplex using decomposition : Application to aircrew scheduling, European Journal of Operational Research, vol.263, pp.1007-1018, 2017.

D. W. Rosen, Design for additive manufacturing: A method to explore unexplored regions of the design space, Eighteenth Annual Solid Freeform Fabrication Symposium, pp.402-415, 2007.

I. Rouen, Fabrication additive métallique : technologies et opportunités, 2015.

B. Roy, Classement et choix en présence de points de vue multiples, RAIRO -Operations Research -Recherche Opérationnelle, vol.2, pp.57-75, 1968.

B. Roy, The outranking foundations aproach and the methods, Theory and Decision, vol.31, pp.49-73, 1991.

B. Roy, Decision science or decision aid science?, European Journal of Operational Research, vol.66, pp.184-203, 1993.

B. Roy, Robustness in operational research and decision aiding: A multi-faceted issue, European Journal of Operational Research, vol.200, issue.3, pp.629-638, 2010.

R. Rubinstein, The Cross-Entropy Method for Combinatorial and Continuous Optimization, Methodology and Computing in Applied Probability, vol.1, pp.127-190, 1999.

R. Y. Rubinstein, Optimization of computer simulation models with rare events, European Journal of Operational Research, pp.89-112, 1997.

M. Ruffo and R. Hague, Cost estimation for rapid manufacturing simultaneous production of mixed components using laser sintering, Proceedings of the Institution of Mechanical Engineers, pp.1585-1591, 2007.

M. Ruffo, C. Tuck, and R. Hague, Cost estimation for rapid manufacturing -Laser sintering production for low to medium volumes, Proceedings of the Institution of Mechanical Engineers, vol.220, issue.9, pp.1417-1427, 2006.

B. Rusjan, Model for manufacturing strategic decision making, International Journal of Operations & Production Management, vol.25, issue.8, pp.740-761, 2005.

T. L. Saaty, The Analytic Hierarchy Process (McGraw Hil), 1980.

T. L. Saaty, The analytic hierarchy process -What it is and how it is used, Mathematical Modelling, vol.9, issue.3, pp.161-176, 1987.

T. L. Saaty, How to make a decision : The Analytic Hierarchy Process, European Journal of Operational Research, vol.48, pp.9-26, 1990.

T. L. Saaty, The Analytic Network Process, 2005.

M. Salvator and P. Gondé, Gestion des assurances de l'entreprise (CLET), 1981.

L. Savage, The foundations of statistics (Courier Do), 1972.

A. Schärlig, Décider sur plusieurs critères -Panorama de l'aide à la décision multicritère, 1985.

M. Schröder, B. Falk, and R. Schmitt, Evaluation of cost structures of additive manufacturing processes using a new business model, 7th Industrial Product-Service Systems Conference, vol.30, pp.311-316, 2015.

M. Sevaux and S. Dauzere-peres, A Genetic Algorithm to Minimize the weighted number of late jobs on a single machine, European Journal of Operational Research, 2000.

A. Shabbir, Semiconductor tool planning via multi-stage stochastic programming, Proceedings of the International Conference on Modeling and Analysis in Semiconductor Manufacturing, vol.153, p.157, 2002.

T. A. Silva, M. C. Souza, and . De, Surgical scheduling under uncertainty by approximate dynamic programming. Omega, (xxxx), 2019.

H. Simon, Administrative behavior, AJN The American Journal of Nursing, vol.50, issue.2, pp.46-47, 1950.

J. Simos, Evaluer l'impact sur l'environnement: Une approche originale par l'analyse multicritère et la négociation, 1990.

G. Singh, D. , and K. , Comparison of Multi-Modal Optimization Algorithms, pp.1305-1312, 2006.

A. Sioud, Approches hybrides pour la resolution d'un problème d'ordonnancement industriel, 2011.

P. Smets, Varieties of Ignorance and the Need for Well-founded Theories, Information Sciences, pp.135-144, 1991.

M. Solimanpur, J. , and A. , Optimal solution for the two-dimensional facility layout problem using a branch-and-bound algorithm, Computers & Chemical Engineering, vol.55, pp.606-619, 2008.

,

G. Sölveling, C. , and J. , Scheduling of airport runway operations using stochastic branch and bound methods, Transportation Research Part C: Emerging Technologies, vol.45, pp.119-137, 2014.

R. Sreedevi and H. Saranga, International Journal of Production Economics Uncertainty and supply chain risk : The moderating role of supply chain fl exibility in risk mitigation, International Journal of Production Economics, vol.193, pp.332-342, 2015.

J. Sun, Z. Peng, W. Zhou, J. Yhfuh, G. Hong et al., A Review on 3D Printing for Customized Food Fabrication, 43rd Proceedings of the North Maerican Manufacturing Research Institution of SME, vol.1, pp.308-319, 2015.

P. Sureeyatanapas, K. Sriwattananusart, T. Niyamosoth, W. Sessomboon, A. et al., Supplier selection towards uncertain and unavailable information : An extension of TOPSIS method, Operations Research Perspectives, vol.5, pp.69-79, 2018.

J. M. Swaminathan, Tool capacity planning for semiconductor fabrication facilities under demand uncertainty, European Journal of Operational Research, 2000.

M. Syrjakow and H. Szczerbicka, Optimization of simulation models with REMO, European Simulation Multiconference, pp.1-3, 1994.

J. Tacnet, Prise en compte de l'incertitude dans l'expertise des risques naturels en montagne par analyse multicritères et fusion d'information, 2009.

I. C. Trelea, The particle swarm optimization algorithm: Convergence analysis and parameter selection, Information Processing Letters, vol.85, issue.6, pp.447-454, 2003.
URL : https://hal.archives-ouvertes.fr/hal-01313364

E. Triantaphyllou, Using the analytic hierarchy process for decision making in engineering applications : Some challenges, International Journal of Industrial Engineering : Applications and Practice, pp.35-44, 1995.

P. K. Tripathy, R. K. Dash, and C. R. Tripathy, A dynamic programming approach for layout optimization of interconnection networks. Engineering Science and Technology, an International Journal, vol.18, pp.374-384, 2015.

D. A. Van-veldhuizen and G. B. Lamont, Multiobjective evolutionary algorithm research: A history and analysis, pp.1-88, 1998.

J. C. Vansnick, On the problem of weights in multiple criteria decision making (the noncompensatory approach), European Journal of Operational Research, vol.24, issue.2, pp.90051-90053, 1986.

J. Verhulst, Analyse de l'état et de l'avenir du marché de l'impression 3D, 2015.

P. Vincke, L'aide multicritère à la décision (Éditions d), 1989.

K. Wang, A resource portfolio model for equipment investment and allocation of semiconductor testing industry, European Journal of Operational Research, vol.179, pp.390-403, 2007.

,

L. Wang, A hybrid genetic algorithm -neural network strategy for simulation optimization, Applied Mathematics and Computation, vol.170, pp.1329-1343, 2005.

G. Wäscher, H. Haußner, and H. Schumann, An improved typology of cutting and packing problems, European Journal of Operational Research, vol.183, pp.1109-1130, 2007.

L. Wei, Q. Hu, A. Lim, and Q. Liu, A best-fit branch-and-bound heuristic for the unconstrained twodimensional non-guillotine cutting problem, European Journal of Operational Research, vol.270, pp.448-474, 2018.

C. Weller, R. Kleer, and F. T. Piller, Economic implications of 3D printing: Market structure models in light of additive manufacturing revisited, International Journal of Production Economics, vol.164, pp.43-56, 2015.

G. White and D. Lynskey, Economic Analysis of Additive Manufacturing for Final Products: an Industrial Approach, pp.1-11, 2013.

J. Wikner and M. Rudberg, Introducing a customer order decoupling zone in logistics decision-making, International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management, pp.221-224, 2005.

J. O. Wilson, Selection for rapid manufacturing under epistemic uncertainty, 2006.

W. Xie and N. V. Sahinidis, A branch-and-bound algorithm for the continuous facility layout problem, Computers & Chemical Engineering, vol.32, pp.1016-1028, 2008.

F. Xu, H. T. Loh, and Y. S. Wong, Considerations and selection of optimal orientation for different rapid prototyping systems, Rapid Prototyping Journal, 1999.

S. S. Yang, F. Yang, K. Wang, C. , and Y. , Optimising resource portfolio planning for capital-intensive insutries under process-technology progress, International Journal of Production Research, pp.37-41, 2009.

M. F. Yegul, F. S. Erenay, Y. , and M. , Improving configuration of complex production lines via simulation-based optimization, Computers & Industrial Engineering, 2017.

E. L. Yu and P. N. Suganthan, Ensemble of niching algorithms, Information Sciences, vol.180, pp.2815-2833, 2010.

J. M. Yunker and J. D. Tew, Simulation optimization by genetic search, Mathematics and Computers in Simulation, vol.37, issue.1, pp.17-28, 1994.

L. A. Zadeh, Fuzzy sets. Information and Control, vol.8, p.90241, 1965.

T. Zellweger, Time horizon, costs of equity capital, and generic investment strategies of firms, Family Business Review, vol.20, issue.1, pp.1-15, 2007.

Y. Zhang and A. Bernard, Generic build time estimation model for parts produced by SLS, International Conference on Advanced Research in Virtual and Rapid Prototyping, 2013.

Y. Zhang, R. K. Gupta, and A. Bernard, Two-dimensional placement optimization for multi-parts production in additive manufacturing, Robotics and Computer, pp.102-117, 2016.
URL : https://hal.archives-ouvertes.fr/hal-02381241

E. Zitzler, K. Deb, and L. Thiele, Comparison of Multiobjective Evolutionary Algorithms : Empirical Results, Evolutionary Computation, vol.8, pp.173-195, 2000.

M. Zlochin, M. Birattari, N. Meuleau, and M. Dorigo, Model-Based Search for Combinatorial Optimization : A Critical Survey, Annals of Operations Research, vol.131, pp.373-395, 2004.

, La poudre est dans des conteneurs Une quantité fixe est mise au départ. Un réapprovisionnement peut être nécessaire si un plateau n'est plus conforme

, Approvisionner en plateforme Contrôler la qualité de la poudre Produire Contrôleur Machines de test de la granulométrie Exigences qualité? La pièce est entièrement produite sur une seule et même machine

, Une pièce est produite à partir d'un même conteneur

, Carte d'identité (Partie 3) USED AT: ANALYST: DATE: WORKING REVIEWER: DATE: PROJECT: DRAFT NOTES: REV: RECOMMENDED RELEASED UOB UOB Name UOB Label : N°Objects: 17 Facts: Constraints: Resources: Description: UOB UOB Name UOB Label : N°Objects: 18 Facts: Constraints: Resources: Description: UOB UOB Name UOB Label : N°Objects: 19 Facts: Constraints: Resources: Description: UOB UOB Name UOB Label : N°Objects: 20 Facts: Constraints: Resources: Description: UOB UOB Name UOB Label : N°Objects: 22 Facts: Constraints: Resources: Description: UOB UOB Name UOB Label : N°Objects: 24 Facts: Constraints: Resources: Description: UOB UOB Name UOB Label : N°Objects: 25 Facts: Constraints: Resources: Description: UOB UOB Name UOB Label : N°Objects: 29 Facts: Constraints: Resources: Description: CONTEXT-SETTING ITEM DESCRIBED: FORM TYPE: REFERENCE: Scenario 1, vol.3

P. Stocker-la,

, Le transport ne peut pas être manuel. La manutention des pièces dans l'espace de travail implique des contraintes ergonomiques. Nettoyer l'ensemble pièce / plateforme Nettoyer le système de filtration Machine de FA A chaque, Un plateau en acier pèse 30kg. Un plateau complet pèse 350kg dont 200kg de poudre