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South African Journal of Industrial Engineering

On-line version ISSN 2224-7890
Print version ISSN 1012-277X

S. Afr. J. Ind. Eng. vol.21 n.1 Pretoria  2010

 

FEATURE ARTICLES

 

A review of manufacturing resources planning models under different uncertainties: State-of-the-art and future directions

 

 

M.A. WazedI; S. AhmedII; Y. NukmanIII

IDepartment of Engineering Design and Manufacture, University of Malaya, Malaysia. awazed@gmail.com
IIDepartment of Engineering Design and Manufacture, University of Malaya, Malaysia. ahmed@um.edu.my
IIIDepartment of Engineering Design and Manufacture, University of Malaya, Malaysia. nukman@um.edu.my

 

 


ABSTRACT

The main purposes of this paper are to enhance the understanding of manufacturing resources planning models under uncertain conditions by documenting the current state of affairs, and to stimulate a fruitful future research direction by identifying gaps between the relevant issues and the literature available in reputable journals. This paper is a comprehensive and up-to-date review of the existing literature on manufacturing resource planning models under uncertainty. The authors have found that the combined effects/ impacts of the uncertainty factors on the system parameters have yet to be thoroughly studied. So far no research has been conducted into developing mathematical model(s) to study the uncertainty issues holistically in multi-period, multiple product, and multi-stage environments for manufacturing resources planning in association with commonality.


OPSOMMING

Die primêre doel van hierdie artikel is om die insig in vervaardigingshulpbronbeplanning onder onsekerheid te bevorder. Die huidige stand van sake word ondersoek en gapings word uitgewys aan die hand van literatuur beskikbaar in gesaghebbende joernale. Die outeurs bevind in die studie dat die sisteemparameters en die invloed van onsekerheid daarop nog nie voldoende bestudeer is nie. Geen navorsing is nog onderneem om wiskundige modelle te ontwikkel om op holistiese wyse die impak van onsekerheid in multi-periode, veelvoudige produk en multi-stadium omgewing te bestudeer nie.


 

 

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REFERENCES

[1] Koh, S.C.L. & Saad, S.M 2006. Managing uncertainty in ERP-controlled manufacturing environments in SMEs, International Journal of Production Economics, 101(1), pp. 109-127.         [ Links ]

[2] Hopp, W.J. & Spearman, M.L. 1996. Factory physics: Foundations of manufacturing management, 2nd ed., London: Irwin.         [ Links ]

[3] Vollmann, T.E. , Berry, W.L. & Whybark, D.C. 1988. Manufacturing planning and control systems, 2nd ed., Homewood, IL.: APICS, The Educational Society for Resource Management.         [ Links ]

[4] Enns, S.T., 2001. MRP performance effects due to lot size and planned lead-time settings, International Journal of Production Research, 39(3), pp. 461-480.         [ Links ]

[5] Koh, S.C.L. & Saad, S.M. 2003. A holistic approach to diagnose uncertainty in ERP-controlled manufacturing shop floor, International Journal of Production Planning and Control, 14(3), pp. 273-289.         [ Links ]

[6] Buxey, G., 1989. Production scheduling: Practice and theory, European Journal of Operational Research, 39(1), pp. 17-31.         [ Links ]

[7] Krajewski, L.J. & Ritzman, L.P. 1993. Operations management strategy and analysis, 3rd ed, Reading, MA: Addison-Wesley.         [ Links ]

[8] Spitter, J.M., De Kok, A.G & Dellaert, N.P. 2005. Timing production in LP models in a rolling schedule, International Journal of Production Economics, 93-94, pp. 319-329.         [ Links ]

[9] Adbinour-Heml, S., Legnick-Hall, M.L. & Legnick-Hall, C.A. 2003. Pre-implementation attitudes and organizational readiness for implementing an Enterprise Resource Planning System, European Journal of Operational Research, 146(2), pp. 258-273.         [ Links ]

[10] Nah, F.F.H. 2002. Enterprise resource planning solutions and management, Hershey, PA, USA: Idea Group Inc. (IGI).         [ Links ]

[11] Koh, S.C.L. & Gunasekaran, A. 2006. A knowledge management approach for managing uncertainty in manufacturing, Industrial Management & Data Systems, 106(4), pp. 439-459.         [ Links ]

[12] Koh, S.C.L. & Saad, S.M, 2003. MRP controlled manufacturing environment disturb by uncertainty, Robotics and Computer Integrated Manufacturing, 19, pp. 157-171.         [ Links ]

[13] Figliola, R.S. & Beasley, D.E. 1991. Theory and design for mechanical measurement, New York, USA: John Wiley & Sons.         [ Links ]

[14] Yen, B.C. & Tung, Y. 1993. Reliability and uncertainty analysis in hydraulic design, New York, USA: ASCE Publishers.         [ Links ]

[15] Ayyub, B.M. & Gupta, M.M. 1994. Uncertainty modeling and analysis: Theory and applications: North-Holland-Elsevier Scientific Publishers        [ Links ]

[16] Zhao, K., Glover, K. & Doyle, J.C. 1995. Robust and optimal control: Prentice Hall.         [ Links ]

[17] Obercampf, W.L., DeLand, S.M., Rutherford, B.M., Diegert, K.V. & Alvin, K.F. 1999. A new methodology for the estimation of total uncertainty in computational simulation, AIAA Non-Deterministic Approaches Forum, pp. 3061-3083.         [ Links ]

[18] Delaurentis, D.A. & Mavris, D.N. 2000. Uncertainty modeling and management in multidisciplinary analysis and synthesis, 38th Aerospace Sciences Meeting & Exhibition, pp. AIAA 2000-0422.         [ Links ]

[19] Zimmermann, H.J. 2001. Fuzzy set theory and its applications, 4th ed., Dordrecht and Boston: Lauwer Academic Publishers.         [ Links ]

[20] Lindau, R.A. & Lumsden, K.R. 1995. Action taken to prevent the propagation of disturbances in manufacturing systems, International Journal of Production Economics, 41(1-3), pp. 241-248.         [ Links ]

[21] Frizelle, G., McFarlane, D. & Bongaerts, L. 1998. Disturbance measurement in manufacturing production systems, Proceedings of the Advanced Summer Institute of the Esprit Network of Excellence in Intelligent Control and Integrated Manufacturing Systems, pp. 159-162.         [ Links ]

[22] Saad S.M. & Gindy, N.N. 1998. Handling internal and external disturbances in responsive manufacturing environments, International Journal of Production Planning and Control, 9(8), pp. 760-770.         [ Links ]

[23] Koh, S.C.L. & Saad, S.M. 2002. Development of a business model for diagnosing uncertainty in ERP environments, International Journal of Production Research, 40(13), pp. 3015-3039.         [ Links ]

[24] Koh, S.C.L. 2004. MRP-controlled batch-manufacturing environment under uncertainty, Journal of the Operational Research Society, 55, pp. 219-232.         [ Links ]

[25] Mula, J., Poler, R., Garcia-Sabater, J.P. & Lario, F.C. 2006. Models for production planning under uncertainty: A review, International Journal of Production Economics, 103, pp. 271-285.         [ Links ]

[26] "Uncertainty, BusinessDictionary.com," July 8, 2008; http://www.businessdictionary.com/definition/uncertainty.html.         [ Links ]

[27] Ho, C.J. 1989. Evaluating the impact of operating environments on MRP system nervousness, International Journal of Production Research, 27(7), pp. 1115-1135.         [ Links ]

[28] Ayyub, B.M. & Chao, R.U. 1997. Uncertainty modeling in civil engineering with structural and reliability applications, Uncertainty modeling and analysis in civil engineering, pp. 3-33, Boca Raton, FL.: CRC Press.         [ Links ].

[29] Hazelrigg, G.A. 1996. Systems engineering: An approach to information-based design, Upper Sahhle River, NJ: Prentice Hall.         [ Links ]

[30] Du, X. & Chen, W. 2000. Methodology for managing the effect of uncertainty in simulation based design, AIAA Journal, 38(8), pp. 1471-1478.         [ Links ]

[31] Gu, X., Renaud, J.E. & Batill, S.M. 1998. An investigation of multidisciplinary design subject to uncertainties, 7th AIAA/USAF/NASA/ISSMO Multidisciplinary Analysis & Optimization Symposium, pp. 309-319.         [ Links ]

[32] Sommer, G. 1981. Applied systems and cybernetics, Fuzzy inventory scheduling, New York: Academic Press.         [ Links ]

[33] Miller, W.A., Leung, L.C., Azhar, I.M. & Sagent, S. 1997. Fuzzy production planning model for fresh tomato packing, International Journal of Production Economics, 53(3-4), pp. 227-238.         [ Links ]

[34] Hsu, H. & Wang, W. 2001. Possibilistic programming in production planning of assemble-to-order environments, Fuzzy Sets and Systems, 119(1), pp. 59-70.         [ Links ]

[35] Reynoso, G., Grabot, B., Geneste, L. & Vérot, S. 2002. Integration of uncertain and imprecise orders in MRPII, Ninth International Multi-Conference on Advanced Computer Systems, Conference on Production System Design, Supply Chain Management & Logistics.         [ Links ]

[36] Ould-Louly, M.A. & Dolgui, A. 2004. The MPS parameterization under lead time uncertainty, International Journal of Production Economics, 90, pp. 369-376.         [ Links ]

[37] Mohebbi, E. & Choobineh, F. 2005. The impact of component commonality in an assemble-to-order environment under supply and demand uncertainty, Omega, The International Journal of Management Science, 33, pp. 472-482.         [ Links ]

[38] Brennan, L. & Gupta, S.M. 1993. A structured analysis of material requirements planning systems under combined demand and supply uncertainty, International Journal of Production Research, 31(7), pp. 1689-1707.         [ Links ]

[39] Dolgui, A. & Ould-Louly, M.A. 2002. A model for supply planning under lead time uncertainty, International Journal of Production Economics, 78, pp. 145-152.         [ Links ]

[40] Huang, P.Y., Clayton, E.R. & Moore, L.J. 1982. Analysis of material and capacity requirements with Q-GERT, International Journal of Production Research, 20(6), pp. 701-713.         [ Links ]

[41] Mayer, M. & Nusswald, M. 2001. Improving manufacturing costs and lead times with quality-oriented operating curves, Journal of Materials Processing Technology, 119(1-3), pp. 83-89.         [ Links ]

[42] Ho, C.J., Law, W.K. & Rampal, R. 1995. Uncertainty dampening methods for reducing MRP system nervousness, International Journal of Production Research, 33(2), pp. 483-496.         [ Links ]

[43] Billington, P.J., McClain, J.O. & Thomas, L.J. 1983. Mathematical programming approaches to capacity-constrained MRP systems: Review formulation and problem reduction, Management Science, 29(10), pp. 1126-1141.         [ Links ]

[44] Güllü, R., Önol, E. & Erkip, N. 1999. Analysis of an inventory system under supply uncertainty, International Journal of Production Economics, 59(1-3), pp. 377-385.         [ Links ]

[45] Huang, P.Y., Rees, L.P. & Taylor, B.W. 1985. Integrating the MRP-based control level and the multistage shop level of a manufacturing system via network simulation, International Journal of Production Research, 23(6), pp. 1217-1231.         [ Links ]

[46] Dalal, A.J. & Alghalith, M. 2009. Production decisions under joint price and production uncertainty, European Journal of Operational Research, 197(1), pp. 84-92.         [ Links ]

[47] Kim, J. & Gershwin, S.B. 2005. Integrated quality and quantity modeling of a production line, OR Spectrum, 27(2-3), pp. 287-314.         [ Links ]

[48] Kim, H.J. & Hosni, Y.A. 1998. Manufacturing lot-sizing under MRP II environment: An improved analytical model & a heuristic procedure, Computers Ind. Engng, 35(3-4), pp. 423-426.         [ Links ]

[49] Bourland, K.E. & Yano, C.A. 1994. The strategic use of capacity slack in the economic lot scheduling problem with random demand, Management Science, 40(12), pp. 1690-1704.         [ Links ]

[50] Ho, C.J. & Carter, P.L. 1996. An investigation of alternative dampening procedures to cope with MRP system nervousness, International Journal of Production Research, 34(1), pp. 137-156.         [ Links ]

[51] Escudero, L.F. & Kamesam, P.V. 1993. MRP modelling via scenarios, Optimization in Industry, T. A. Ciriani & R. C. Leachman, eds., pp. 101-111: John Wiley & Sons.         [ Links ]

[52] Vargas, G.A. & Metters, R. 1996. Adapting lot-sizing techniques to stochastic demand through production scheduling policy, IIE Transactions, 28(2), pp. 141-148.         [ Links ]

[53] Kira, D., Kusy, M. & Rakita, I. 1997. A stochastic linear programming approach to hierarchical production planning, Journal of Operations Research Society, 48, pp. 207-211.         [ Links ]

[54] Grabot, B., Geneste, L., Reynoso-Castillo, G & Vérot, S. 2005. Integration of uncertain and imprecise orders in the MRP method, Journal of Intelligent manufacturing, 16, pp. 215-234.         [ Links ]

[55] Mula, J., Poler, R. & Garcia, J.P. 2006. MRP with flexible constraints: A fuzzy mathematical programming approach, Fuzzy Sets and Systems, 157, pp. 74-97.         [ Links ]

[56] Balakrishnan, J. & Cheng, C.H. 2007. Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions, European Journal of Operational Research, 177(1), pp. 281-309.         [ Links ]

[57] Mula, J., Poler, R. & Garcia-Sabater, J.P. 2007. Material Requirement Planning with fuzzy constraints and fuzzy coefficients, Fuzzy Sets and Systems, 158, pp. 783793.         [ Links ]

[58] Anosike, A.I. & Zhang, D.Z. 2007. An agent based approach for integrating manufacturing operations, International Journal of Production Economics, pp. doi:10.1016/ j.ijpe.2006.10.013.         [ Links ]

[59] Arruda, E.F. & Do Val, J.B.R. 2008. Stability and optimality of a multi-product production and storage system under demand uncertainty, European Journal of Operational Research, 188(2), pp. 406-427.         [ Links ]

[60] Ben-Daya, M. & Noman, S.M. 2008. Integrated inventory and inspection policies for stochastic demand, European Journal of Operational Research, 185(1), pp. 159-169.         [ Links ]

[61] Grubbstrom, R.W., 1999. A net present value to approach to safety stocks in a multi-level MRP system, International Journal of Production Economics, 59(1-3), pp. 361-375.         [ Links ]

[62] Agatz, N.A.H., Fleischmann, M. & Van Nunen, J.A.E.E. 2008. E-fulfillment and multi-channel distribution - A review, European Journal of Operational Research, 187(2), pp. 339-356.         [ Links ]

[63] Ahmed, S., King, A. & Parija, G., 2003. A multi-stage stochastic integer programming approach for capacity expansion under uncertainty, Journal of Global Optimization, 26, pp. 3-24.         [ Links ]

[64] Mukhopadhyay, S.K. & Ma, H. 2009. Joint procurement and production decisions in remanufacturing under quality and demand uncertainty, International Journal of Production Economics, 120(1), pp. 5-17.         [ Links ]

[65] Tang, O. & Grubbstrbm, R.W. 2002. Planning and replanning the master production schedule under demand uncertainty, International Journal of Production Economics, 78(3), pp. 323-334.         [ Links ]

[66] Lan, C.H. & Lan, T.S. 2005. A combinatorial manufacturing resource planning model for long-term CNC machining industry, International Journal of Advanced Manufacturing Technology, 26, pp. 1157-1162.         [ Links ]

[67] Leung, S.C.H., Tsang, S.O.S, Ng, W.L. & Wu, W.L. 2007. A robust optimization model for multi-site production planning problem in an uncertain environment, European Journal of Operational Research, 181, pp. 224-238.         [ Links ]

[68] Shabbir, A., Alan, J.K. & Gyana, P. 2003. A multi-stage stochastic integer programming approach for capacity expansion under uncertainty, Journal of Global Optimization, 26(1), pp. 3-24.         [ Links ]

[69] Xu, H.M. & Li, D.B. 2007. A meta-modeling paradigm of the manufacturing resources using mathematical logic for process planning, International Journal of Advanced Manufacturing Technology.         [ Links ]

[70] Sanmartí, E., Espuña, A. & Puigjaner, L. 1995. Effects of equipment failure uncertainty in batch production scheduling, Computers & Chemical Engineering, 19 (Supplement 1), pp. 565-570.         [ Links ]

[71] Anosike, A.I. & Zhang, D.Z. 2009. An agent-based approach for integrating manufacturing operations, International Journal of Production Economics, 121(2), pp. 333-352.         [ Links ]

[72] Koh, S.C.L., Saad, S.M. & Jones, M.H. 2002. Uncertainty under MRP-planned manufacture: Review and categorisation, International Journal of Production Research, 40(10), pp. 2399-2421.         [ Links ]

[73] Guide, V.D.R. & Srivastava, R. 2000. A review of techniques for buffering against uncertainty with MRP systems, Production Planning & Control, 11(3), pp. 223-233.         [ Links ]

[74] Heese, H.S. & Swaminathan, J.M. 2006. Product line design with component commonality and cost-reduction effort, Manufacturing & Service Operations Management, 8(2), pp. 206-219.         [ Links ]

[75] Manners, W. 1990. Classification and analysis of uncertainty in structural system, Proceedings of the 3rd IFIPWG7.5 Conference on Reliability and Optimization of Structural Systems, pp. 251-260.         [ Links ]

[76] Laskey, K.B. 1996. Model uncertainty: Theory and practical implications, IEEE Transactions on System, Man, and Cybernetics - Part A: System and Human, 26(3), pp. 340-348.         [ Links ]

[77] Lawrence, S.R. & Sewell, E.C. 1997. Heuristics, optimal, static, and dynamic schedules when processing times are uncertain, Journal of Operations Management, 15(1), pp. 71-82.         [ Links ]

[78] Swamidass, P.M. & Newell, W.T. 1987. Manufacturing strategy, environmental uncertainty and performance: A path analytic model, Management Science, 33(4), pp. 509-524.         [ Links ]

[79] Koh, S.C.L., Jones, M.H., Saad, S.M., Arunachalam, S. & Gunasekaran, A. 2000. Measuring uncertainties in MRP environments, Logistics Information Management: An International Journal, 13(3), pp. 177-183.         [ Links ]

[80] Sridharan, V. & LaForge, R.L. 1989. The impact of safety stock on schedule instability, cost and service, Journal of Operations Management, 8, pp. 327-347.         [ Links ]

[81] Buzacott, J.A. & Shanthikumar, J.G. 1994. Safety stock versus safety lead-time in MRP controlled production systems, Management Science, 40, pp. 1678-1689.         [ Links ]

[82] Pagell, M. & Krause, D.R. 1999. A multiple-method study of environmental uncertainty and manufacturing flexibility, Journal of Operations Management, 17(3), pp. 307-325.         [ Links ]

[83] Enns, S.T. 2002. MRP performance effects due to forecast bias and demand uncertainty, European Journal of Operational Research, 138(1), pp. 87-102.         [ Links ]

[84] Newman, W.R., Hanna, M. & Maffei, M.J., 1993. Dealing with the uncertainties of manufacturing: Flexibility, buffers and integration, International Journal of Operations & Production Management, 13(1), pp. 19-34.         [ Links ]

[85] Prater, E., Biehl, M. & Smith, M.A. 2000. International supply chain agility -tradeoffs between flexibility and uncertainty, International Journal of Operations & Production Management, 21(5/6), pp. 823-839.         [ Links ]

[86] Molinder, A. 1997. Joint optimization of lot-sizes, safety stocks and safety lead times in an MRP system, International Journal of Production Research, 35(4), pp. 983-994.         [ Links ]

[87] Lew, J.S., Keel, L.H. & Juang, J.N. 1994. Quantification of parametric uncertainty via an interval model, Journal of Guidance, Control and Dynamics, 17(6), pp. 1212-1218.         [ Links ]

[88] Moore, R.E. 1966. Interval analysis, Englewood Cliffs, NJ: Prentice Hall.         [ Links ]

[89] Simoff, S.J. 1996. Handling uncertainty in neural networks: An interval approach, Proceedings of International Conference on Neural Networks, I, pp. 606-610.         [ Links ]

[90] Chen, S.H., Wu, J. & Chen, Y.D. 2004. Interval optimization for uncertain structures, Finite Elements in Analysis and Design, 40(11), pp. 1379-1398.         [ Links ]

[91] Chen, R. & Ward, A.C. 1997. Generalizing interval matrix operations for design, Journal of Mechanical Design, 119(1), pp. 65-72.         [ Links ]

[92] Kubota, S. & Hori, O. 1999. Uncertainty model of the gradient constraint and quantitative reliability measures of optical flow, Systems and Computers in Japan, 30(7), pp. 9-19.         [ Links ]

[93] Penmetsa, R.C. & Grandhi, R.V. 2002. Efficient estimation of structural reliability for problems with uncertain intervals, Computers and Structures, 80(12), pp. 1103-1112.         [ Links ]

[94] Lindberg, H.E. 1992. Convex models for uncertain imperfection control in multi-mode dynamic buckling, Journal of Applied Mechanics, 59(4), pp. 937-945.         [ Links ]

[95] Ben-Haim, Y. 1994. Non-probabilistic concept of reliability, Structural Safety, 14(4), pp. 227-245.         [ Links ]

[96] Ben-Haim, Y. 1996. Robust reliability in mechanical sciences, Berlin, Germany: Springer-Verlag.         [ Links ]

[97] Ben-Haim, Y. 1997. Robust reliability of structures, Advances in Applied Mechanics, 33(1), pp. 1-40.         [ Links ]

[98] Attoh-Okine, N.O. 2002. Uncertainty analysis in structural number determination in flexible pavement design - A convex model approach, Construction and Building Materials, 16(2), pp. 67-71.         [ Links ]

[99] Zadeh, L.A. 1965. Fuzzy sets, Information and Control, 8(3), pp. 338-353.         [ Links ]

[100] Wood, K.L. & Antonsson, E.K. 1989. Computations with imprecise parameters in engineering design: Background and theory, Journal of Mechanisms, Transmissions and Automation in Design, 111(4), pp. 616-625.         [ Links ]

[101] Wood, K.L., Antonsson, E.K. & Beck, J.L. 1989. Comparing fuzzy and probability calculus for representing imprecision in preliminary engineering design, Proceedings of the 1st International Conference on Design Theory and Methodology, 17, pp. 99-105.         [ Links ]

[102] Wood, K.L., Otto, K.N. & Antonsson, E.K. 1992. Engineering design calculations with fuzzy parameters, Fuzzy Sets and Systems, 52(1), pp. 1-20.         [ Links ]

[103] Deng, J. 1989. Introduction to grey system theory, Journal of Grey System, 1(1), pp. 1-24.         [ Links ]

[104] Pawlak, Z. 1985. Some remarks on rough sets, Bulletin of the Polish Academy of Sciences: Technical Sciences, 33(11-12), pp. 567-572.         [ Links ]

[105] Chung, C.H. & Krajewski, L.J. 1984. Planning horizons for master production scheduling, Journal of Operations Management, 4(4), pp. 389-406.         [ Links ]

[106] Belvaux, G. & Wolsey, L.A. 2001. Modelling practical lot-sizing problems as mixed integer programs, Management Science, 47(7), pp. 993-1007.         [ Links ]

[107] Harris, B., Lewis, F. & Cook, D.J. 2002. A matrix formulation for integrating assembly trees and manufacturing resource planning with capacity constraints, Journal of Intelligent Manufacturing, 13, pp. 239-252.         [ Links ]

[108] Choi, S. & Enns, S.T. 2004. Multi-product capacity-constrained lot sizing with economic objectives, International Journal of Production Economics, 91(1), pp. 47-62.         [ Links ]

[109] Lusa, A., Corominas, A. & Munóz, N. 2008. A multistage scenario optimisation procedure to plan annualised working hours under demand uncertainty, International Journal of Production Economics, 113(2), pp. 957-968.         [ Links ]

[110] Sarker, B.R., Jamal, A.M.M. & Mondal, S. 2008. Optimal batch sizing in a multistage production system with rework consideration, European Journal of Operational Research, 184(3), pp. 915-929.         [ Links ]

[111] Cárdenas-Barrón, L.E. 2009. On optimal batch sizing in a multi-stage production system with rework consideration, European Journal of Operational Research, 196(3), pp. 1238-1244.         [ Links ]

[112] Dobos, I. & Richter, K. 2004. An extended production/recycling model with stationary demand and return rates, International Journal of Production Economics, 90(3), pp. 311-323.         [ Links ]

[113] Dobos, I. & Richter, K. 2006. A production/recycling model with quality consideration, International Journal of Production Economics, 104(2), pp. 571-579.         [ Links ]

[114] Kogan, K. & Lou, S. 2003. Multi-stage newsboy problem: A dynamic model, European Journal of Operational Research, 149(2), pp. 448-458.         [ Links ]

[115] Leung, K.N.F. 2009. An integrated production-inventory system in a multi-stage multi-firm supply chain, Transportation Research Part E: Logistics and Transportation Review, In press, corrected proof        [ Links ]

[116] Chen, S.H. & Chang, S.M. 2008. Optimization of fuzzy production inventory model with unrepairable defective products, International Journal of Production Economics, 113(2), pp. 887-894.         [ Links ]

 

 

* Corresponding author
1 The author is a PhD candidate at the Department of Engineering Design and Manufacture, University of Malaya.

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