. Un-coût-d, acquisition (en e) correspondant au transfert de propriété des pièces, 2. un coût de transport (en e) correspondant au coût de déplacement des pièces de la zone d'approvisionnement à la zone de production, 3. un coût d'emballage (en e) correspondant à l'utilisation de transconteneur pour le transport maritime

U. Coût-de-transport, lié aux livraisons en urgence (taxi, hélicoptère) pouvant survenir lors d'un aléa de transport, un incident 'qualité' ou une surconsommation, 5. un coût de douane (en e) lors du changement d'union douanière, 6. des frais de stock de fonctionnement (en e) correspondant au stock pour pallier aux aléas du transport intercontinental, 7. des frais d'encours (en e) correspondant à l'immobilisation dûe au temps de transport, 8. des frais de stock de sécurisation

. De-même, sont utilisés pour valoriser les ux de distribution Ces éléments sont indépendants de la période mais seront actualisés pour prendre en compte la dépréciation monétaire. Les classes étudiées et leurs relations sont synthétisés en gure 3.1. Notons que les aspects temporels sont intégrés dans ce modèle via la description de tableaux indéxés par la période ; par exemple, quantite_f lux_distri[h] pour les quantités de ux distribués à une période h donnée, ABHT95] [Mar05] [PRI06] [SSP08] [FFH06] [DBX06] [Hic99] [YYEC03] [WLR + 05] [KR00] [LHHA06] [SB00] [KS99] [VMB06] [HFHA08] [FS04] [TBP08] [CFL09] [MNSdG06] [CPS06] [PMD04] [JJCP02]

]. Le-tableaujp01, utilisation de ces méthodes dans les modèles sélectionnés Si plusieurs méthodes sont cochées, cela signie la mise en place d'un couplage entre ces méthodes. Les méthodes de résolution sont majoritairement des méthodes exactes (75% des articles), c'està-dire de la PL ou de la PLNE souvent implémentée avec un solveur commercial (CPLEX, LINGO, X-PRESS...). Des méthodes d'accélération sont mises en place pour les problèmes de grande taille

. La-seconde-partie-est-composée-d-'une-première-matrice, h?H,t?T P,u?ZP où HR t,u correspond à la décision d'investissement à la période h de la ressource de production de la technologie de production t sur la zone de production u. Nous avons aussi une seconde matrice (HS h,p,s ) h?H,p?F P,s?ZA où HS h,p,s correspond à la décision d'investissement à la période h de la source d'approvisionnement de la famille de pièces p sur la zone d'approvisionnement s. Pour ces deux matrices

. La-gure-3, 10 donne un exemple des diérents voisinages sur les sources d'approvisionnement. La gure 3

L. Données-concernant and . Possibilités, Toutes les possibilités d'achat, de production, de stockage sont générées en dénissant des seuils minimaux de possibilité au niveau de chaque site concerné (par exemple, pour chaque usine, une matière première est disponible au niveau de 75% de ses fournisseurs) Une procédure similaire est présentée dans

. Matrice-d-'incidence-entre-les-n÷uds, Toutes les liaisons entre les diérents sites sont générées entre les niveaux successifs (entre les fournisseurs et les usines, les usines et les plateformes...) et sans transport direct

. Au-nal, 450 instances ont été générées à partir des 15 types d'instances classées dans les 3 familles de ratio charge/capacité (donc 45 sous-familles) avec 10 générations aléatoires par sous-familles

. Notre-problème-est-relativement-diérent, Ensuite le réseau logistique considéré ne prend pas en compte les plateformes logistiques De plus, les investissements ne sont pas tout le temps pris en compte. Enn, au niveau des coûts et en dehors de l'aspect stockage non traité, nous prenons en compte la douane de manière plus réaliste avec l'application d'un véritable taux de douane sur le prix de cession. Cependant des éléments peuvent être repris : La distinction des types de clients pour la génération des demandes, L'utilisation de seuils pour s'assurer la diversité de possibilités d'achat et de production. La méthode d'obtention des réseaux avec une certaine densité, L'utilisation des demandes pour générer les capacités de production

. Ensuite, des familles de véhicules suivantes seront en bi-sourcing (les distributions de ces familles de véhicules auront deux zones de production capable de les satisfaire). Enn, les familles de véhicules restantes auront des distributions nécessitant une seule zone de production pouvant les servir. La répartition des productions privilégie les zones qui n'ont aucune production puis répartie aléatoirement les productions

C. Audet, J. Brimberg, P. Hansen, S. L. Digabel, and N. Mladenovi¢, Pooling Problem: Alternate Formulations and Solution Methods, Références bibliographiques, p.761776, 2004.
DOI : 10.1287/mnsc.1030.0207

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.426.3141

S. [. Almutairi and . Elhedhli, A new Lagrangean approach to the pooling problem, Journal of Global Optimization, vol.3, issue.3, p.237257, 2009.
DOI : 10.1007/s10898-008-9371-1

M. [. Arsham, M. I. Gradisar, and . Stemberger, Linearly constrained global optimization: a general solution algorithm with applications, Applied Mathematics and Computation, vol.134, issue.2-3, p.345361, 2003.
DOI : 10.1016/S0096-3003(01)00289-2

A. [. Amrani, N. Martel, P. Zuerey, and . Makeeva, A variable neighborhood search heuristic for the design of multicommodity productiondistribution networks with alternative facility congurations, OR Spectrum, p.119, 2009.

R. N. Anthony, Planning and control systems : a framework for analysis. Division of Research, 1965.

R. H. Ballou, Business logistics/supply chain management : planning, organizing, and controlling the supply chain, 2004.

T. E. Baker and L. S. Lasdon, Successive linear programming at Exxon. Management science, p.264274, 1985.
DOI : 10.1287/mnsc.31.3.264

J. [. Byrd, R. A. Nocedal, and . Waltz, KNITRO : An integrated package for nonlinear optimization. Large-scale nonlinear optimization, p.3559, 2006.

M. [. Cortinhal and . Captivo, Upper and lower bounds for the single source capacitated location problem, European Journal of Operational Research, vol.151, issue.2, p.333351, 2003.
DOI : 10.1016/S0377-2217(02)00829-9

. [. Chan, S. Chung, and . Wadhwa, A hybrid genetic algorithm for production and distribution, Omega, vol.33, issue.4, p.345355, 2005.
DOI : 10.1016/j.omega.2004.05.004

J. [. Chauhan, L. Frayret, and . Lebel, Multi-commodity supply network planning in the forest supply chain, European Journal of Operational Research, vol.196, issue.2, p.688696, 2009.
DOI : 10.1016/j.ejor.2008.03.024

C. Chandra and J. Grabis, Supply chain conguration : concepts, solutions, and applications, 2007.

M. Christopher, Logistics and supply chain management : creating value-added networks, Financial Times, 2005.

S. [. Cohen and . Moon, An integrated plant loading model with economies of scale and scope, European Journal of Operational Research, vol.50, issue.3, pp.266279-152, 1991.
DOI : 10.1016/0377-2217(91)90260-3

S. Chopra and P. Meindl, Supply Chain Management. Strategy, Planning & Operation, 2001.
DOI : 10.1007/978-3-8349-9320-5_22

N. [. Castro and . Nabona, An implementation of linear and nonlinear multicommodity network ows, European Journal of Operational Research, vol.92, issue.1, p.3753, 1996.

L. Cooper, Heuristic Methods for Location-Allocation Problems, SIAM Review, vol.6, issue.1, pp.37-53, 1964.
DOI : 10.1137/1006005

S. S. Chauhan and J. M. Proth, The concave cost supply problem, European Journal of Operational Research, vol.148, issue.2, p.374383, 2003.
DOI : 10.1016/S0377-2217(02)00407-1

F. [. Cordeau, M. M. Pasin, and . Solomon, An integrated model for logistics network design, Annals of Operations Research, vol.98, issue.3, p.5982, 2006.
DOI : 10.1007/s10479-006-0001-3

K. L. Croxton, Modeling and solving network ow problems with piecewise linear costs, with applications in supply chain management, 1999.

O. [. Coriat and . Weistein, Herbert Simon et la rationalité limitée, Les nouvelles théories économiques, p.16, 1995.

]. W. Dbg-+-07, O. Dullaert, M. Braysy, B. Goetschalckx, A. Raa et al., Supply chain (re) design : Support for managerial and policy decisions, European Journal of Transport and Infrastructure Research, vol.7, issue.2, p.7392, 2007.

L. [. Ding, X. Benyoucef, and . Xie, A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization, Engineering Applications of Artificial Intelligence, vol.19, issue.6, p.609623, 2006.
DOI : 10.1016/j.engappai.2005.12.008

URL : https://hal.archives-ouvertes.fr/emse-00449373

P. Dornier and M. Fender, La logistique globale et le Supply Chain Management. Edition d'organisation, 2007.

E. Escudero, G. Galindo, E. Garcia, V. Gomez, and . Sabau, Schumann, a modeling framework for supply chain management under uncertainty, European Journal of Operational Research, vol.119, issue.1, p.1434, 1999.
DOI : 10.1016/S0377-2217(98)00366-X

S. [. Fleischmann, P. Ferber, and . Henrich, Strategic Planning of BMW???s Global Production Network, Interfaces, vol.36, issue.3, p.194208, 2006.
DOI : 10.1287/inte.1050.0187

J. [. Fontes and . Gonçalves, Heuristic solutions for general concave minimum cost network ow problems, Networks, vol.50, issue.1, p.6776, 2007.

L. [. Fontes and . La, On minimum concave cost network ow problems, 2006.

]. B. Fle93 and . Fleischmann, Designing distribution systems with transport economies of scale

J. W. Forrester, Industrial dynamics, 1961.

M. [. Fandel and . Stammen, A general model for extended strategic supply chain management with emphasis on product life cycles including development and recycling, International Journal of Production Economics, vol.89, issue.3, p.293308, 2004.
DOI : 10.1016/S0925-5273(03)00198-1

B. Gendron, T. G. Crainic, and A. Frangioni, Multicommodity capacitated network design , volume Telecommunications Network Planning, 1998.
DOI : 10.1007/978-1-4615-5087-7_1

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.2849

[. Gen, J. Choi, and K. Ida, Improved genetic algorithm for generalized transportation problem, Artificial Life and Robotics, vol.25, issue.2, p.96102, 2000.
DOI : 10.1007/BF02480863

]. P. Gen03 and . Genin, Planication tactique robuste avec usage d'un APS Proposition d'un mode de gestion par plan de référence, 2003.

M. Goetschalckx, B. Fleischmann, P. Gourgand, and . Kellert, Strategic network design Conception d'un environnement de modélisation des systèmes de production, Troisième congrès de international de Génie Industriel, 2001.

V. [. Gruat-la-forme, J. P. Botta-genoulaz, and . Campagne, The role of APS systems in Supply Chain Management : a theoretical and industrial analysis, International Journal of Logistics Systems and Management, vol.5, issue.3, p.356374, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00266984

M. Grotschel, L. Lovasz, and A. Schrijver, Geometric algorithms and combinatorial optimization, 1993.

E. Goldratt, Critical Chain : A Business Novel, 1997.

P. [. Guisewite and . Pardalos, Minimum concave-cost network ow problems : Applications, complexity, and algorithms, Annals of Operations Research, vol.25, issue.1, p.7599, 1990.
DOI : 10.1007/bf02283688

R. [. Georion and . Powers, Twenty years of strategic distribution system design : An evolutionary perspective, Interfaces, vol.25, issue.5, p.105127, 1995.

C. [. Goetschalckx, K. Vidal, and . Dogan, Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms, European Journal of Operational Research, vol.143, issue.1
DOI : 10.1016/S0377-2217(02)00142-X

S. [. Graves and . Willems, Optimizing Strategic Safety Stock Placement in Supply Chains, Manufacturing & Service Operations Management, p.6883, 2000.
DOI : 10.1287/msom.2.1.68.23267

T. Harrison, Principles for the strategic design of supply chains in The practice of supply chain management : where theory and application converge, p.3

]. J. Hen99 and . Hennet, From the aggregate plan to lot-sizing in multi-level production planning

Y. [. Hammami, A. B. Frein, and . Hadj-alouane, Supply chain design in the delocalization context: Relevant features and new modeling tendencies, International Journal of Production Economics, vol.113, issue.2, p.641656, 2008.
DOI : 10.1016/j.ijpe.2007.10.016

]. D. Hic99 and . Hicks, A four step methodology for using simulation and optimization technologies in strategic supply chain planning, Proceedings of the 31st conference on Winter simulation : Simulationa bridge to the future, pp.1215-1220, 1999.

[. Hsu and H. Li, An integrated plant capacity and production planning model for high-tech manufacturing firms with economies of scale, International Journal of Production Economics, vol.118, issue.2, pp.486-500, 2009.
DOI : 10.1016/j.ijpe.2008.09.015

H. [. Hax, Hierarchical Integration of Production Planning and Scheduling, Logistics : TIMS Studies in Management Sciences, vol.1, p.5360, 1975.
DOI : 10.1007/978-3-642-27922-5_19

M. Holweg, F. K. Pil, and T. Christiansen, The second century : reconnecting customer and value chain through build-to-order : moving beyond mass and lean production in the auto industry, 2004.

[. Ilog, Logicnet plus xe, 2009.

S. [. Ilich and . Simonovic, An evolution program for non-linear transportation problems, Journal of Heuristics, vol.7, issue.2, p.145168, 2001.

P. A. Jensen and J. W. Barnes, Network ow programming, 1980.

A. [. Jawahar and . Balaji, A genetic algorithm for the two-stage supply chain distribution problem associated with a xed charge, European Journal of Operational Research, vol.194, issue.2, p.496537, 2009.

[. Jda, Network & inventory optimization, 2009.

Y. [. Joly, D. Frein, V. Gauthier, and . Bernier, Etude de l'impact des blocages sur le ux de production d'une usine terminale automobile, Journal européen des systèmes automatisés, vol.38, pp.3-4291313, 2004.

S. [. Jang, B. M. Jang, J. Chang, and . Park, A combined model of network design and production/distribution planning for a supply network, Computers & Industrial Engineering, vol.43, issue.1-2, p.263281, 2002.
DOI : 10.1016/S0360-8352(02)00074-8

[. Ji, Z. Jin, and H. Tang, An improved simulated annealing for solving the linear constrained optimization problems, Applied Mathematics and Computation, vol.183, issue.1, pp.251-259, 2006.
DOI : 10.1016/j.amc.2006.05.070

H. [. Jayaraman and . Pirkul, Planning and coordination of production and distribution facilities for multiple commodities, European Journal of Operational Research, vol.133, issue.2, p.394408, 2001.
DOI : 10.1016/S0377-2217(00)00033-3

B. [. Kelly and . Khumawala, Capacitated warehouse location with concave costs, Journal of the Operational Research Society, vol.33, p.817826, 1982.

Z. [. Koziel and . Michalewicz, Evolutionary Algorithms, Homomorphous Mappings, and Constrained Parameter Optimization, Evolutionary Computation, vol.26, issue.3, p.1944, 1999.
DOI : 10.1162/evco.1996.4.1.1

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.8813

J. Kallrath and T. I. , Real optimization with SAP APO, 2006.

P. [. Kim and . Pardalos, A solution approach to the fixed charge network flow problem using a dynamic slope scaling procedure, Operations Research Letters, vol.24, issue.4, pp.195-203, 1999.
DOI : 10.1016/S0167-6377(99)00004-8

M. [. Kouvelis and . Rosenblatt, A mathematical programming model for global supply chain management : Conceptual approach and managerial insights. Supply Chain Management : Models, Applications, and Research Directions, 2000.

H. [. Koksalan and . Sural, Efes Beverage Group Makes Location and Distribution Decisions for Its Malt Plants, Interfaces, vol.29, issue.2, p.89103, 1999.
DOI : 10.1287/inte.29.2.89

K. [. Lamothe, M. Hadj-hamou, and . Aldanondo, An optimization model for selecting a product family and designing its supply chain, European Journal of Operational Research, vol.169, issue.3, p.10301047, 2006.
DOI : 10.1016/j.ejor.2005.02.007

URL : https://hal.archives-ouvertes.fr/hal-00452961

. Llamasoft, Supply chain guru, 2009.

A. [. Larsson, M. Migdalas, and . Ronnqvist, A Lagrangean heuristic for the capacitated concave minimum cost network ow problem, European journal of operational research, vol.78, issue.1, p.116129, 1994.

H. Lourenco, Supply Chain Management, Economics Working Papers, vol.36, 2001.
DOI : 10.1057/jos.2014.25

A. Langevin and D. Riopel, Logistics systems : design and optimization, 2005.
DOI : 10.1007/b106452

T. [. Le-thi and . Pham-dinh, A continuous approach for the concave cost supply problem via DC programming and DCA, Discrete Applied Mathematics, vol.156, issue.3, pp.325-338, 2008.
DOI : 10.1016/j.dam.2007.03.024

-. Aps, Supply Chain Magazine Synthèse de l'ore aps, 2009.

A. Martel, Conception de réseaux logistiques globaux. Cours MBA gestion manufacturière et logistique : Conception et Gestion de chaînes logistiques, p.287300

]. A. Mar05 and . Martel, The design of production-distribution networks : A mathematical programming approach, APPLIED OPTIMIZATION, vol.98, p.265, 2005.

]. P. Mck75 and . Mckeown, A vertex ranking procedure for solving the linear xed-charge problem, MD01] S. Melkote and M.S. Daskin. Capacitated facility location/network design problems, p.11831191, 1975.

C. [. Misener and . Floudas, Advancces for the pooling problem -modeling, global optimization and computational studies, Appl. Comput. Math, vol.8, issue.1, p.322, 2009.

V. [. Meixell and . Gargeya, Global supply chain design: A literature review and critique, Transportation Research Part E: Logistics and Transportation Review, vol.41, issue.6, p.41531550, 2005.
DOI : 10.1016/j.tre.2005.06.003

H. [. Melachrinoudis and . Min, The dynamic relocation and phase-out of a hybrid, twoechelon plant/warehousing facility : A multiple objective approach Capacitated multicommodity network ow problems with piecewise linear concave costs, European Journal of Operational Research IIE Transactions, vol.123, issue.17, pp.115-36683696, 2000.

A. Martel, W. Barek, and S. Amours, L'inuence des facteurs internationaux sur la compétitivité des réseaux de création de valeur multinationaux : le cas des compagnies canadiennes de pâtes et papiers, p.3185, 2006.
DOI : 10.3917/riges.313.0085

URL : http://www.cairn.info/load_pdf.php?ID_ARTICLE=RIGES_313_0085

M. Melo, S. Nickel, F. Saldanha, and . Gama, Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning, Computers & Operations Research, vol.33, issue.1, p.181208, 2006.
DOI : 10.1016/j.cor.2004.07.005

M. Melo, S. Nickel, F. Saldanha-da, and . Gama, Facility location and supply chain managementA review, European Journal of Operational Research, vol.196, issue.2, p.401412, 2009.

]. S. Moo89 and . Moon, Application of generalised benders decomposition to a non linear distribution system design problem, Naval Research Logistics, vol.36, p.283295, 1989.

]. K. Mur68, ]. Murtynp08, P. Nahapetyan, and . Pardalos, Solving the xed charge problem by ranking the extreme points Adaptive dynamic cost updating procedure for solving xed charge network ow problems, Operations Research Computational Optimization and Applications, vol.16, issue.391, p.2682793750, 1968.

. Opt09 and . Optiant, Power chain, 2009.

P. [. Perron, S. L. Hansen, N. Digabel, and . Mladenovi¢, Exact and heuristic solutions of the global supply chain problem with transfer pricing, Pim01] Y. Pimor. Logistique, Techniques et mises en ceuvre, 2001.
DOI : 10.1016/j.ejor.2009.06.018

A. [. Paquet, G. Martel, and . Desaulniers, Including technology selection decisions in manufacturing network design models, Poi09] Prot Point. Protnetwork, p.117125, 2004.
DOI : 10.1016/S0377-2217(97)80080-X

]. M. Por98, . [. Porter, F. Pirard, S. Riane, and . Iassinovski, Competitive advantage : Creating and sustaining superior performance Une démarche hybride d'aide à la decision pour la reconguration et la planication strategique des réseaux logistiques des entreprises multi-sites, Conférence MOSIM'06, 1998.

. Quintiq, Quintiq strategic planner, 2009.

A. [. Riopel, J. F. Langevin, and . Campbell, The network of logistics decisions Logistical Systems : Design and Optimization, RNP09] S. Rebennack, A. Nahapetyan, and P.M. Pardalos. Bilinear modeling solution approach for xed charge network ow problems. Optimization Letters, p.138347355, 2005.

]. N. Sah96, . H. Sahinidis-[-sb00-]-e, B. M. Sabri, and . Beamon, BARON : A general purpose global optimization software package A multi-objective approach to simultaneous strategic and operational planning in supply chain design, Journal of Global Optimization Omega, vol.8, issue.25, pp.201205-28581598, 1996.

N. [. Suon, S. Grangeon, O. Norre, and . Gourguechon, Conguration de réseaux logistiques approvisionnement, production et distribution : Etat de l'art, JDJN MACS, 2009.

M. Suon, N. Grangeon, S. Norre, and O. Gourguechon, A hybrid metaheuristic for a strategic supply chain planning problem with procurement-production-distribution activities and economy of scale, Proceedings of the 3rd International Conference on Information Systems, Logistics and Supply Chain Creating value through green supply chains ILS 2010, 2010.

M. Suon, N. Grangeon, S. Norre, and O. Gourguechon, Une problème de planication stratégique de type production-distribution avec économies d'échelles et technologies de production, 8e Conférence Internationale de MOdélisation et SIMulation, MOSIM10, 2010.

J. Sharma, Extensions and special cases of transportation problem : A survey Stadtler and C. Kilger. Supply chain management and advanced planning : concepts, models, software, and case studies, SK08] H. Stadtler and C. Kilger. Supply Chain Management and Advanced Planning, p.928940, 2005.

P. [. Simchi-levi, E. Kaminsky, ]. R. Simchi-levisol74, and . Soland, Designing and Managing the Supply Chain Optimal facility location with concave costs, Operations Research, vol.22, issue.2, p.373382, 1974.

[. M. Smith, C. C. Pantelides, R. Sousa, N. Shah, and L. G. Papageorgiou, Supply chain network optimization Supply chain design and multilevel planning -An industrial case, Global optimisation of nonconvex MINLPs. Computers and Chemical Engineering Computers and Chemical Engineering, vol.21, issue.11, pp.791796-3226432663, 1997.

N. [. Thanh, O. Bostel, and . Péton, A dynamic model for facility location in the design of complex supply chains, International Journal of Production Economics, vol.113, issue.2, pp.678-693, 2008.
DOI : 10.1016/j.ijpe.2007.10.017

URL : https://hal.archives-ouvertes.fr/hal-00308588

K. Terefe, Nonlinear transportation problems, 2007.

C. Thierry, A. Thomas, and G. Bel, Simulation for Supply Chain Management, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00326868

T. E. Vollmann, W. L. Berry, D. C. Whybark, and F. R. Jacobs, Manufacturing planning and control systems for supply chain management, 2005.

C. [. Visweswaran and . Floudas, A Global Optimization Algorithm(GOP) for certain classes of nonconvex NLPsII. Application of theory and test problems, Computers & Chemical Engineering, vol.14, issue.12, p.14191434, 1990.

C. J. Vidal and M. Goetschalckx, A global supply chain model with transfer pricing and transportation cost allocation, European Journal of Operational Research, vol.129, issue.1, pp.134-158, 2001.
DOI : 10.1016/S0377-2217(99)00431-2

A. [. Vila, R. Martel, and . Beauregard, Designing logistics networks in divergent process industries: A methodology and its application to the lumber industry, International Journal of Production Economics, vol.102, issue.2, p.358378, 2006.
DOI : 10.1016/j.ijpe.2005.03.011

A. Vaz and L. Vicente, PSwarm : a hybrid solver for linearly constrained global derivative-free optimization. Optimization Methods and Software, p.669685, 2009.

]. W. Wlr-+-05, D. Wilhelm, B. Liang, D. Rao, X. Warrier et al., Design of international assembly systems and their supply chains under NAFTA, Transportation Research Part E, issue.6, p.41467493, 2005.

J. [. Waltz and . Nocedal, KNITRO user's manual, 2003.

H. [. Yao and . Hsu, A new spanning tree-based genetic algorithm for??the??design of multi-stage supply chain networks with nonlinear transportation costs, Optimization and Engineering, vol.54, issue.3, p.219237, 2009.
DOI : 10.1007/s11081-008-9059-x

S. [. Yan and . Luo, Probabilistic local search algorithms for concave cost transportation network problems, European Journal of Operational Research, vol.117, issue.3, p.511521, 1999.
DOI : 10.1016/S0377-2217(98)00270-7

Z. [. Yan, E. Yu, and . Cheng, A strategic model for supply chain design with logical constraints: formulation and solution, Computers & Operations Research, vol.30, issue.14, p.21352155, 2003.
DOI : 10.1016/S0305-0548(02)00127-2

N. [. Zhang, L. Kim, and . Lasdon, An Improved Successive Linear Programming Algorithm, Management Science, vol.31, issue.10, p.3113121331, 1985.
DOI : 10.1287/mnsc.31.10.1312

S. [. Zhang and . Wang, Linearly constrained global optimization via piecewise-linear approximation, Journal of Computational and Applied Mathematics, vol.214, issue.1, p.111120, 2008.
DOI : 10.1016/j.cam.2007.02.006

URL : http://doi.org/10.1016/j.cam.2007.02.006