References
[1] Y. Chang, H. Makatsoris, Supply chain modelling using simulation. Int. J. Simul. Syst.
Sci. Technol. 2(1) (2001) 24-30. 12J H. Mohammadi Bidhandi, R.M. Yusuff, M.M.H. Megat Ahmed, M.R. Abu Bakar, Development of a new approach for deterministic supply chain network design, Eur. J. Opcr. Res. 198(1) (2009) 121-128.
13] A.M. Sarmiento, R. Nagi, A review of integrated analysis of production-distribution systems, HE Trans. 31(11) (1999) 1061-1074.
14] F. Persson, J. Olhager, Performance simulation of supply chain designs. Int. J. Prod. Econ. 77(3) (2002) 231-245.
15] A. Muriel, D. Simchi-Levi, Supply chain design and planning—applications of optimization techniques for strategic and tactical models, in: A.G. de Kok. S.C. Graves (Eds.), Handbooks in Operations Research and Management Science, (Volume 11), Elsevier, 2003, pp. 15-93.
[6| S.S. Pitty, W. Li. A. Adhitya, R. Srinivasan. I.A. Karimi, Decision support for integrated refinery supply chains: Part I. Dynamic simulation, Comput. Chem. Eng. 32(1 1)
(2008) 2767-2786.
17] M.S. Sajadieh, M.R.A. Jokar, M. Modarres, Developing a coordinated vendor-buyer model in two-stage supply chains with stochastic lead-times, Comput. Oper. Res. 36(8)
(2009) 2484-2489.
|8| S.W. Ryu, K.K. Lee, A stochastic inventory model of dual sourccd supply chain with
lead-time reduction. Int. J. Prod. Econ. 81-82 (2003) 513-524. [9] E. Eskigun, R. Uzsoy. P.V. Prcckel, G. Beaujon, S. Krishnan, J.D. Tew, Outbound supply chain network design with mode selection, lead times and capacitated vehicle distribution centers, Eur. J. Oper. Res. 165(1) (2005) 182-206. [I0J M. Leng, M. Parlar, Lead-time reduction in a two-level supply chain: non-cooperative equilibria vs. coordination with a profit-sharing contract. Int. J. Prod. Econ. 118(2)
(2009) 521 -544.
[1 lj D.J. Thomas, P.M. Griffin. Coordinated supply chain management, Eur. J. Oper. Res. 94(1) (1996) 1-15.
[12] A.M.N. Lair, An Integrated Model for Optimising Manufacturing and Distribution Network Scheduling, Ph.D. Thesis, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia. Adelaide, 2008, p. 266.
113] C. Siirie, M. Wagner. Supply chain analysis, in: H. Stadtler, C. Kilger (Eds.), Supply Chain Management and Advanced Planning: Concepts, Models. Software, and Case Studies, Springer, Heidelberg, Berlin. 2005.
114] J. Banks, Getting Started with AutoMod, second ed„ Brooks Automation, Inc., Chelmsford. MA, 2004 (permission of John Wiley & Sons, Inc.).
[15| D.W. Jordan. P. Smith. Mathematical Techniques: An Introduction for the Engineering. Physical, and Mathematical Sciences, third ed.. OUP. Oxford. 2002.
[16] J.W. Chinneck. Binary and mixed-integer programming, in: Practical Optimization: A Gentle Introduction, Carleton University: Ottawa. Ontario, Canada. 2004 (Chapter 13).
[17] J.W. Chinneck, Introduction, in: Practical Optimization: A Gentle Introduction, Carleton University: Ottawa, Ontario, Canada, 2004 (Chapter 1).
118] M. Chen. W. Wang, A linear programming model for integrated steel production and distribution planning. Int. J. Oper. Prod. Manage. 17(6) (1997) 592-610.
119] A. Kanyalkar. G. Adil. An integrated aggregate and detailed planning in a multi-site production environment using linear programming. Int. J. Prod. Res. 43(20) (2005) 4431-4454.
[20] A. Kanyalkar, G. Adil. Aggregate and detailed production planning integrating procurement and distribution plans in a multi-site environment. Int. J. Prod. Res. 45(22) (2007) 5329-5353.
[21 ] A. Kanyalkar. G. Adil, A robust optimisation model for aggregate and detailed planning of a multi-site procurement-production-distribution system. Int. J. Prod. Res. 48(3)
(2010) 635-656.
[22] T.-F. Liang, Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain, Comput. lnd. Eng. 55(3) (2008) 676-694.
[23] K.S. Bhutta, F. Huq, G. Frazier. Z. Mohamed, An integrated location, production, distribution and investment model for a multinational corporation. Int. J. Prod. Econ. 86 (3) (2003) 201-216.
[24] J. Fcrrio, J. Wassick, Chemical supply chain network optimization. Comput. Chem. Eng. 32(11) (2008) 2481-2504.
25] H. Gunnarsson, M. Ronnqvist, D. Carlsson, Integrated production and distribution planning for Sodra Cell AB. J. Math. Model. Algorithms 6(1) (2007) 25-45.
26] M. Hamcdi. R. Farahani Zanjirani, M.M. Husseini, G.R. Esmaeilian, A distribution planning model for natural gas supply chain: a case study. Energy Policy 37(3) (2009) 799-812.
27] A.N. Haq. P. Vrat, A. Kanda, An integrated production-inventory-distribution model for manufacture of urea: a case. Int. J. Prod. Econ. 25(1-3) (1991) 39-49.
28] Y. Kim, C. Yun, S.B. Park, S. Park. L.T. Fan, An integrated model of supply network and production planning for multiple fuel products of multi-site refineries, Comput. Chem. Eng. 32(11) (2008) 2529-2535.
29J Z.M. Mohamed. An integrated production-distribution model for a multi-national company operating under varying exchange rates. Int. J. Prod. Econ. 58(1) (1999) 81—92.
T. Paksoy. H. Kiirsat Gules, D. Bayraktar, Design and optimization of a strategic production-distribution model for supply chain management: case study of a plastic profile manufacturer in Turkey, Sel^uk J. Appl. Math. 8(2) (2007) 83-99.
P. Tsiakis, L.G. Papageorgiou, Optimal production allocation and distribution supply chain networks. Int. J. Prod. Econ. 111(2) (2008) 468-483.
H. Yan, Z. Yu. T.C.E. Cheng. A strategic model for supply chain design with logical constraints: formulation and solution, Comput. Opcr. Res. 30(14) (2003) 2135-2155.
H. Selim, C. Araz, I. Ozkarahan, Collaborative production-distribution planning in supply chain: a fuzzy goal programming approach. Transp. Res. Part E Logistics Transp. Rev. 44(3) (2008) 396-419.
K. Demirli and A.D. Yimer, Production-distribution planning with fuzzy costs, in: NAFIPS 2006—Annual Meeting of the North American Fuzzy Information Processing Society, 2006.
C.-L. Chen, W.-C. Lee. Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices, Comput. Chem. Eng. 28(6—7) (2004) 1131-1 144.
C. Dhaencns-Flipo, G. Finke, An integrated model for an industrial production-distribution problem, HE Trans. 33 (2001) 705-715.
B. Bilgen, Application of fuzzy mathematical programming approach to the production allocation and distribution supply chain network problem. Expert Syst. Appl. 37(6) (2010) 4488-4495.
K. Das, S. Sengupta. A hierarchical process industry production-distribution planning model, Int. J. Prod. Econ. 117(2) (2009) 402-419.
39J N. Rizk, A. Martcl, S. D'Amours. Multi-item dynamic production-distribution planning in process industries with divergent finishing stages, Comput. Opcr. Res. 33(12) (2006) 3600-3623.
40] G. Barbarosoglu, D. Ozgur. Hierarchical design of an integrated production and 2-eche- lon distribution system. Eur. J. Oper. Res. 118(3) (1999) 464-484.
41] V Jayaraman, H. Pirkul. Planning and coordination of production and distribution facilities for multiple commodities, Eur. J. Oper. Res. 133(2) (2001) 394-408.
42] T. ^ishi, M. Konishi, M. Ago, A distributed decision making system for integrated optimization of production scheduling and distribution for aluminum production line, Comput. Chem. Eng. 31(10) (2007) 1205-1221.
43] S.S Syam, A model and methodologies for the location problem with logistical components, Comput. Oper. Res. 29(9) (2002) 1173-1193.
44] J. Xu, Y. He, M. Gen, A class of random fuzzy programming and its application to supply chain design, Comput. Ind. Eng. 56(3) (2009) 937-950.
| Integration in Logistics Planning and Optimization 391 |
390 Logistics Operations and Management
[45] A.M. Geoffrion. A guided tour of recent practical advances in integer linear programming, Omega 4(1) (1976) 49-57.
[46] G.B. Dantzig, Linear programming, Oper. Res. 50( 1) (2002) 42-47.
[47] M.L. Fisher, An applications oriented guide to Lagrangian relaxation. Interfaces 15(2) (1985) 10-21.
148] C.A. Mendez. J. Cerda, I.E. Grossmann, I. Harjunkoski, M. Fahl, State-of-the-art review of optimization methods for short-term scheduling of batch processes, Comput. Chem. Eng. 30(6-7) (2006) 913-946.
[49] B. Park, H. Choi, M. Kang, Integration of production and distribution planning using a genetic algorithm in supply chain management, in: Analysis and Design of Intelligent Systems Using Soft Computing Techniques, 2007, pp. 416-426.
[50] J.W. Chinneck, Heuristics for discrete search: genetic algorithms and simulated annealing, in: Practical Optimization: A Gentle Introduction, Carleton University, Ottawa, Ontario. Canada. 2004 (Chapter 14).
[511 V. Jayaraman. A. Ross, A simulated annealing methodology to distribution network design and management, Eur. J. Oper. Res. 144(3) (2003) 629-645.
[52] M.A. Cohen, H.L. Lee, Strategic analysis of integrated production-distribution systems: models and methods. Oper. Res. Soc. Am. 36(2) (1988) 216-228.
[53] J.L. Coronado. An Optimization Model for Strategic Supply Chain Design Under Stochastic Capacity Disruptions, Doctoral Thesis, College of Engineering, Texas A&M University, Texas, 2008. pp. 1-110.
[54] L. Ozdamar. T. Yazgac, A hierarchical planning approach for a production-distribution system. Int. J. Prod. Res. 37(16) (1999) 3759.
[55] D.F. Руке, M.A. Cohen. Performance characteristics of stochastic integrated production-distribution systems, Eur. J. Oper. Res. 68( 1) (1993) 23-48.
[56] D.F. Руке, M.A. Cohen, Multiproduct integrated production-distribution systems, Eur. J. Oper. Res. 74(1) (1994) 18-49.
[57] P. Yilmaz, В. £atay. Strategic level three-stage production distribution planning with capacity expansion, Comput. Ind. Eng. 51(4) (2006) 609-620.
[58] W.-C. Yeh, A hybrid heuristic algorithm for the multistage supply chain network problem. Int. J. Adv. Manuf. Technol. 26 (2005) 675-685.
[59] K. Xing, Design for Upgradability: Modelling and Optimisation, Ph.D. Thesis, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Adelaide, 2006. I
[60] M.J. Tarokh. M. Golkar. Supply chain simulation methods, in: 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI '06, 2006.
[61J E.J. Williams, A. Gunal, Supply chain simulation and analysis with SIMFLEX, in: 2003 Winter Simulation Conference, USA, 2003. J
[62] C. Chung, Simulation Modeling Handbook: A Practical Approach (Industrial and Manufacturing Engineering Series), CRC Press, Boca Raton. FL. 2004.
[63] H. Picrreval, R. Bruniaux, C. Caux, A continuous simulation approach f_ supply chains in the automotive industry, Simul. Model. Pract. Theory 15(2) (200
185-198. Я
|64J H.S. Hwang. G.S. Cho, A performance evaluation model for order picking warehou
design, Comput. Ind. Eng. 51(2) (2006) 335-342. I
[65] D. Burnett, T. LeBaron. Efficiency modeling warehouse systems, in: Proceedings о the 2001 Winter Simulation Conference, 2001.
|66] J H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, University of Michigan Press, Ann Arbor. 1975.
167J K. Ganesh. M. Punniyamoorthy, Optimization of continuous-time production planning using hybrid genetic algorithms-simulated annealing. Int. J. Adv. Manuf. Technol. 26 (2005) 148-154.
[68j B. Fahimnia, Optimisation of Manufacturing Lead-Time, Using Genetic Algorithm, Master's Thesis, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Adelaide, 2006, p. 151.
[69] R.A. Aliev, B. Fazlollahi, B.G. Guirimov, R.R. Aliev, Fuzzy-genetic approach to aggregate production-distribution planning in supply chain management, Inform. Sci. 177 (20) (2007) 4241-4255.
|70] F. Altipannak, M. Gen, L. Lin. A genetic algorithm for supply chain network design, in: 35th International Conference on Computers and Industrial Engineering, 2005.
[71] F. Altiparmak, M. Gen, L. Lin. I. Karaoglan, A steady-state genetic algorithm for multi-product supply chain network design. Comput. Ind. Eng. 56(2) (2007) 531-537.
|72| F. Altiparmak. M. Gen. L. Lin. T. Paksoy, A genetic algorithm approach for multi- objective optimization of supply chain networks. Comput. Ind. Eng. 51(1) (2006) 196-215.
[73] F.T.S. Chan, S.H. Chung. S. Wadhwa, A hybrid genetic algorithm for production and distribution. Omega 33(4) (2005) 345-355.
[74] R.Z. Farahani. M. Elahipanah. A genetic algorithm to optimize the total cost and service level for just-in-time distribution in a supply chain, Int. J. Prod. Econ. 111(2) (2008) 229-243.
[75] M. Gen, A. Syarif, Hybrid genetic algorithm for multi-time period production/distribution planning, Comput. Ind. Eng. 48(4) (2005) 799-809.
176] A. Syarif, Y. Yun. M. Gen, Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach, Comput. Ind. Eng. 43(1-2) (2002) 299-314.
177] A. Tasan, A two step approach for the integrated production and distribution planning of a supply chain. Intel!. Comput. 4113 (2006) 883-888.
[78] W.-C. Yeh, An efficient memetic algorithm for the multi-stage supply chain network problem. Int. J. Adv. Manuf. Technol. 29(7) (2006) 803-813.
[79] A.D. Yimer, K. Demirli, A genetic approach to two-phase optimization of dynamic supply chain scheduling, Comput. Ind. Eng. 58(3) (2009) 411-422.
[80] A. Kazemi, M. Fazel Zarandi, S. Moattar Husseini, A multi-agent system to solve the Production-distribution planning problem for a supply chain: a genetic algorithm approach. Int. J. Adv. Manuf. Technol. 44( 1) (2009) 180-193.
J R. Marian, Optimisation of Assembly Sequences Using Genetic Algorithms, Ph.D. Thesis, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Adelaide, 2003, p. 287.
J B. Sobhi-Najafabadi, Optimal Design of Permanent Magnet Generators. Ph.D. Thesis, School of Electrical and Information Engineering, University of South Australia
Adelaide. 2002, p. 331.
R. Haupt, S. Haupt, Practical genetic algorithms. Discrete Applied Mathematics, John ''еУ & Sons, Inc.. New Jersey, 2004, pp. 1-261.