Abstract
As the result of revolution of modern business management mode, the theory and method of supply chain management is also the most important basic theory in the field of management and the frontier of management science. Chopra et al. (Manag Sci 50(1):8–14, 2004 [1]) in Management Science wrote: “Operation and supply chain are currently the most critical themes in management science and improving the theoretical and practical evolution of management science.”
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References
Chopra S, Lovejoy W, Yano C (2004) Five decades of operations management and the prospects ahead. Manage Sci 50(1):8–14
Houlihan JB (1985) International supply chain management. Int J Phy Distrib Mater Manag 15(1):22–38
Stevens J (1989) Integrating the supply chain. Int J Phys Distrib Mater Manag 19(8):3–8
Saunders MJ (1995) Chains, pipelines, networks and value stream: the role, nature and value of such metaphors in forming perceptions of the task of purchasing and supply management. In: First worldwide research symposium on purchasing and supply chain management. Tempe, Arizona, USA, pp 476–485, Mar 1995
Ellram LM (1991) Supply chain management: the industrial organization perspective. Int J Phys Distrib Logistics Manag 21(1):13–22
Lee HL, Ng SM (1997) Introduction to the special issue on global supply chain management. Prod Oper Manag 6(3):191–192
Lee HL, Billington C (1992) Managing supply chain inventory: pitfalls and opportunities. Sloan Manag Rev 33(3):65–73
Christopher M (2012) Logistics and supply chain management. Pearson, UK
Simchi-Levi D, Kaminsky P, Simchi-Levi E (2003) Designing and managing the supply chain. Irwin/McGraw-Hill, San Francisco
Ma SH, Lin Y, Chen ZX (2005) Supply chain management. Machinery Industry Press, Beijing
Stadtler H (2005) Supply chain management and advanced planning-basics, overview and challenges. Eur J Oper Res 163(3):575–588
Kannan VR, Handfield RB (1998) Supply chain management: supplier performance and firm performance. Int J Purchasing Mater Manag 34(3):2–9
Berry D, Towill DR, Wadsley N (1994) Supply chain management in the electronics product industry. Int J Phys Distrib Mater Manag 24(10):20–32
Kopczak LR (1997) Logistics partnership and supply chain restructuring: survey results from the US computer industry. Prod Oper Manag 6(3):191–192
Chopra S, Meindl P (2001) Supply chain management: strategy, planning, and operation. Tsinghua University Press, Beijing
Huang XY (2007) Supply chain operations—coordination, optimization and control. Science Press, Beijing
Huang XY (2004) Supply chain model and optimization. Science Press, Beijing
Zhang T, Sun LY (2005) Supply chain uncertainty management: technologies and strategies. Tsinghua University Press, Beijing
Verity JW (1996) Clearing the cobwebs from the stockroom. Bus Week 21:140
Bendiner J (1998) Understanding supply chain optimization: from “what if” to what’s best. APICS Perform Advantage 8:34–39
Liu BD, Peng J (2005) Uncertainty theory tutorial. Tsinghua University Press, Beijing
Liu BD (2007) Uncertainty theory, 2nd edn. Springer, Berlin
Li CL, Luo YF (2003) Uncertainty of supply chain management research. Sci Technol Prog Policy 10:84–86
Lee HL, Billington C (1995) The evolution of supply chain management models and practice at Hewllet-Packard. Interfaces 25(5):42–63
Liu BD, Zhao RQ (1998) Stochastic programming and fuzzy programming. Tsinghua University Press, Beijing
Liu BD, Zhao RQ, Wang G (2003) Uncertain programming and applications. Tsinghua University Press, Beijing
Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353
Bellman RE, Zadeh LA (1970) Decision making in a fuzzy environment. Manage Sci 17(4):141–164
Liu B, Liu YK (2002) Expected value of fuzzy variable and fuzzy expected value models. IEEE Transact Fuzzy Syst 10(4):445–450
Li X, Liu B (2006) A sufficient and necessary condition for credibility measures. Int J Uncertainty Fuzziness Knowl Based Syst 14(5):527–535
Zadeh LA (1999) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst 100:9–34
Liu B (2009) Theory and practice of uncertain programming, 2nd edn. Springer, Berlin
Fortemps P, Roubens M (1996) Ranking and defuzzification methods based on area compensation. Fuzzy Sets Syst 82(3):319–330
Kwakernaak H (1978) Fuzzy random variables–I: definitions and theorems. Inf Sci 15(1):1–29
Kwakernaak H (1979) Fuzzy random variables–II: algorithms and examples for the discrete case. Inf Sci 17(3):253–278
Puri ML, Ralescu DA (1983) Differentials of fuzzy functions. J Math Anal Appl 91(2):552–558
Puri ML, Ralescu DA (1986) Fuzzy random variables. J Math Anal Appl 114(2):409–422
Kruse R, Meyer KD (1987) Statistics with vague data. Springer Science & Business Media, Berlin
Liu YK, Liu B (2003) Fuzzy random variables: a scalar expected value operator. Fuzzy Optim Decis Making 2(2):143–160
Cheung RKM, Powell WB (1996) Models and algorithms for distribution problems with uncertain demands. Transp Sci 30(1):43–59
Zak YA, Frank RY (1975) Optimal planning of level of initial reserves and funds for material resources. Avtomatika i Telemekhanika 36(9):99–107
Cohen MA, Moon S (1991) An integrated Plant loading model with economies of scale and scope. Eur J Oper Res 50(3):266–279
Blumenfeld DE, Burns LD, Daganzo CF (1991) Synchronizing production and transportation schedules. Transp Res Part B Methodol 25(1):23–37
Bhatnagar R, Chandra P, Goyal SK (1993) Models for multi-plant coordination. Eur J Oper Res 67(2):141–160
Chien TW (1993) Determining profit-maximizing product/shipping policies in a one-to-one direct shipping, stochastic demand environment. Eur J Oper Res 64(1):83–102
Chandra P, Fisher ML (1994) Coordination of production and distribution planning. Eur J Oper Res 72(3):503–517
Arntzen BC, Brown GG, Harrison TP et al (1995) Global supply chain management at digital equipment corporation. Interfaces 25(1):69–93
Thomas DJ, Griffin PM (1996) Coordinated supply chain management. Eur J Oper Res 94(1):1–15
Cheung RKM, Powell WB (1996) Models and algorithms for distribution problems with uncertain demands. Transp Sci 30(1):43–59
Hill RM (1997) The single-vendor single-buyer integrated production inventory model with a generalized policy. Eur J Oper Res 97(3):493–499
Beamon BM (1998) Supply chain design and analysis: models and methods. Int J Prod Econ 55(3):281–294
Fumero F, Vercellis C (1999) Synchronized development of production, inventory and distribution schedules. Transp Sci 33(3):330–340
Escudero LF, Galindo E, Garcıa G et al (1999) Schumann, a modeling framework for supply chain management under uncertainty. Eur J Oper Res 119(1):14–34
Von Lanzenauer CH, Pilz-Glombik K (2002) Coordinating supply chain decisions: an optimization model. OR Spectrum 24(1):59–78
Bredstrom D, Ronnqvist M (2002) Integrated production planning and route scheduling in pulp mill industry. In: Proceedings of the 35th annual Hawaii international conference on system sciences, HICSS, pp 1606–1614. IEEE, Jan 2002
Gupta A, Maranas CD (2003) Managing demand uncertainty in supply chain planning. Comput Chem Eng 27(8):1219–1227
Luh PB, Ni M, Chen H et al (2003) Price-based approach for activity coordination in a supply network. IEEE Trans Robot Autom 19(2):335–346
Pibernik R, Sucky E (2006) Centralised and decentralised supply chain planning. Int J Integr Supply Manag 2(1):6–27
Peidro D, Mula J, Poler R et al (2009) Quantitative models for supply chain planning under uncertainty: a review. Int J Adv Manuf Techno 43(3–4):400–420
Chen ZH, Wang YF, Ma SH (2000) Management mechanism of supply chain-production planning and control. Ind Eng Manag 5(2):22–25
Zhou JH, Wang DW, Xu Y (2001) Soft computing JIT production planning supply chain of multi-location manufacturing system. Control Dec 16(6):894–897
Zhou JH, Wang DW (2001) Production planning model for supply chain for multi-location plants and distributors. Inf Control 30(2):169–172
Hou KH, Hu ZW (2002) Supply chain planning in supply chain management. Ind Eng J 5(5):21–25
Sun HJ, Gao ZY (2002) Production planning model of two-echelon distribution network in supply chain based on distributed plant. Chin J Manag Sci 10(6):40–43
Yao JM, Zhou GH (2003) Analysis of supply chain optimization planning and scheduling in mass customization. J Manag Sci China 6(5):58–64
Yang HH, Wu ZM (2003) Two-level GA-based approach to the capacitated lot sizing problem for multi-plants supply chain. J Shanghai Jiaotong Univ 37(4):473–478
Zhu BL, Yu HB, Huang XY (2004) Collaboration planning modeling based on game theory for supply chain. J Northeast Univ (Nat Sci) 25(7):703–706
Li JX, Tang LX, Wu HJ (2004) Modeling of the coordinated production planning of a two-stage mineral industry supply Chain. J Northeast Univ (Nat Sci) 25(4):352–355
Li JX, Tang LX, Wu HJ (2005) Collaborative production planning in a three stage steel supply chain. Comput Integr Manuf Syst 11(3):375–380
Chen HL, Zhang J, Ma DZ (2004) Research on supply chain collaborative based on cost and time balance optimization. Comput Integr Manuf Syst 10(12):1518–1522
Ma B, Song FG (2004) The design of supply chain-based garment enterprise integrated planning management system. Comput Syst Appl 9:47–49
Cheng HN, Xiang SG, Yang X et al (2004) Supply chain planning model under uncertainty. Comput Appl Chem 21(1):97–102
Yang WS, Ma SH, Li L (2004) Coordinated planning model based on response time of supply chain. Forecasting 23(5):52–56
Lin ZW, Lin XH, Ding QL (2004) The research of production planning and control for supply chain. Ind Eng 7(4):22–25
Ge J, Li YF, Xia GP (2005) Research on global supply chain production planning under uncertain environment. Comput Integr Manuf Syst 11(8):1120–1126
Zhou W, Jin YH (2005) Coordination method for multi-plant supply chain planning optimization based on augmented Lagrangian relaxation. J Tsinghua Univ (Nat Sci) 45(10):1324–1327
Jiang M (2005) The study of supply chain enterprises’ production planning system resolution model. Mech Des Manuf 12:162–164
Chen ZX (2005) Influence of supply chain information uncertainty on production planning and improving methods. Group Technol Prod Modernization 22(4):10–13
Li YF, Xia GP, Yang YX et al (2005) Global supply chain tactical planning model based on fuzzy stochastic expected value programming. Syst Eng Theory Pract 8:1–9
Wang HJ, Ma SH, Zhao Y (2005) Prototype software system of production planning for mass customization in the supply chain. Ind Eng Manag 10(3):78–81
Yu HF, Wang DW (2005) Food-chain algorithm and application to supply-chain planning. J Syst Simul 17(5):1195–1199
Nie LS, Xu XF, Zhan DC (2006) Collaborative planning in supply chains based on Lagrangian relaxation and genetic algorithm. Comput Integr Manuf Syst 12(11):1869–1875
Kong LF, Luo TD (2006) Agent-based distributed negotiation algorithm for dynamic scheduling problem. Comput Integr Manuf Syst 12(7):1128–1133
Du SF, Liang ML (2006) GBOM-based Supply chain network and its integrated production planning model with capacity constraints. Chin J Manag 3(2):143–147
Su S, Zhan DC, Xu XF (2007) Manufacturing supply chain planning based on extended state task network. J Softw 18(7):1626–1638
Ma SH, Shen W (2007) A planning model and analysis for logistics capability in a multi-stage supply chain. Chin J Manag Sci 15(4):83–88
Shen W, Ma SH (2007) A scheduling model for logistics capability in a time-based multi-stage supply chain. Oper Res Manag Sci 16(3):20–25
Fang XH, Wang WJ, Tang BY (2007) New technology for supply chain integration—collaborative planning forecasting and replenishing. J Donghua Univ (Nat Sci) 33(2):191–195
Ji XL, Zhu HM, Wang NS (2004) Study on three-stage supply chain integrated planning based on GA. J Nanjing Univ Aeronaut Astronaut 36(5):550–555
Xiao L (2007) Distributed model for the process of supply chain logistic plan based on integration of knowledge context. Sci Technol Progr Policy 24(7):132–135
Li JZ, Liu CL (2007) Study on mass customization planning model of cluster supply chain. Industr Eng Manag 12(3):40–46
Zhao JH, Bai JD, Wei XF et al (2007) Fuzzy supply chain problem for lot sizing production planning. Syst Eng Electr 29(8):1299–1304
Cai ZY, Xiao RB, Tan Y et al (2008) Fuzzy adaptive production plan dispatching of cycle supply chain under uncertainty conditions. Control Dec 23(5):525–529
Fu YY, Pan XH (2008) Optimization of multi-part inventory control and production lot under fuzzy uncertainty. J Zhejiang Univ (Eng Sci) 42(6): 1046–1050
Shao XF, Ji JH (2008) Research on pricing and capacity planning coordination based on reimbursement contracts. Chin J Manag Sci 16(4):62–68
Bitran GR, Yanasse HH (1982) Computational complexity of the capacitated lot size problem. Manage Sci 28(10):1174–1186
Chen WH, Thizy JM (1990) Analysis of relaxations for the multi-item capacitated lot sizing problem. Ann Oper Res 26(1):29–72
Karimi B, Ghomi SF, Wilson JM (2003) The capacitated lot sizing problem:a review of models and algorithms. Omega 31(5):365–378
Drexl A, Kimms A (1997) Lot sizing and scheduling-survey and extension. Eur J Oper Res 99(2):221–235
Barany I, Van Roy T, Wolsey LA (1984) Uncapacitated lot-sizing: the convex hull of solutions. Springer, Berlin, pp 32–43
Karni R, Roll Y (1982) A heuristic algorithm for the multi-item lot sizing problem with capacity constraints. IIE Trans 14(4):249–256
Guo QS, Yang XY, Wang XG (2006) System modeling. National Defense Industry Press, Beijing
Minsky M, Papert SA (1969) Perceptrons. MIT Press, Cambridge
Cybenko G (1989) Approximations by superpositions of a sigmoidal function. Math Control Signals Systems 2(4):303–314
Hornik K, Stinchcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2(5):359–366
Liu PY (2003) Regular fuzzy neural network as universal approximator of fuzzy valued function. Control and Decision 18(1):19–28
Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Michigan
Xuan GN, Cheng RW (2004) Genetic algorithms and engineering optimization. Tsinghua University Press, Beijing
Koza JR (1992) Genetic programming. MIT Press, Cambridge
Koza JR, Rice JP (1994) Genetic programming, 2nd edn. MIT Press, Cambridge
Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs, 3rd edn. Springer, Berlin
Raman S, Patnaik LM (1997) Optimization via evolutionary processes. Adv Comput 45:155–196
Tzeng HW, Chen JL, Chen NK (1999) Traffic grooming in WDM networks using genetic algorithm. In: IEEE international conference on systems, man, and cybernetics. IEEE SMC’99 Conference Proceedings, vol 1. IEEE, pp 1003–1006
Golberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison Wesley, Boston
Chen CW, Dong SH, Ding WY (2006) Optimization of multi-stage production planning in ERW pipe manufacturing. J Univ Sci Technol Beijing 28(7):691–695
Vasconcelos JA, Ramirez JA, Takahashi RHC et al (2001) Improvements in genetic algorithms. IEEE Trans Magn 37(5):3414–3417
Wang DW, Fang SC (1996) Just-in-time production planning with semi-infinite programming model and genetic algorithm. Control Deci 11(4):446–451
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Shao, J., Sun, Y., Noche, B. (2015). Literature Review. In: Optimization of Integrated Supply Chain Planning under Multiple Uncertainty. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47250-7_2
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DOI: https://doi.org/10.1007/978-3-662-47250-7_2
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