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How to cite this paper
APA: Singh, S & Gupta, V. (2014). Supply chain production model with preservation technology under fuzzy environment. International Journal of Industrial Engineering Computations, 5(3), 459-474.
Chicago/Turabian: Singh, S & Gupta, V. 2014. "Supply chain production model with preservation technology under fuzzy environment." International Journal of Industrial Engineering Computations 5, no. 3 (2014): 459-474.
AMA: Singh, S & Gupta, V. Supply chain production model with preservation technology under fuzzy environment. International Journal of Industrial Engineering Computations. 2014;5(3):459-474.
References
Bhunia, A.K., Kundu, S., Sannigrahi, T. and Goyal, S.K. (2009). An application of tournament genetic algorithm in a marketing oriented economic production lot-size model for deteriorating items. International Journal of Production Economics, 119(1) 112–121.
Chang, S.C., Yao, J.S. and Lee, H.M. (1998). Economic reorder point for fuzzy backorder quantity. European Journal of Operational Research, 109(1) 183-202.
Chang, H.J. and Lin, W.F. (2010). A partial backlogging inventory model for non-instantaneous deteriorating items with stock-dependent consumption rate under inflation. Yugoslav Journal of Operation Research, 20(1) 35-54.
Chang, C.T., Teng, J.T. and Goyal, S.K. (2010). Optimal replenishment policies for non- instantaneous deteriorating items with stock-dependent demand. International Journal of Production Economics, 123(1) 62–68.
Covert, R.P. and Philip, G.C. (1973). An EOQ model for items with Weibull distribution deterioration. AIIE Transaction, 5(4) 323–326.
Ghare, P.M. and Schrader, G.F. (1963). A model for exponential decaying inventory. Journal of Industrial Engineering, 14(6) 238–43.
Goyal, S.K. and Giri, B.C. (2001). Recent Trends in Modeling of Deteriorating Inventory. European Journal of Operational Research, 134(1) 1–16.
Dave, U. and Patel, L.K. (1981). (T, Si) policy inventory model for deteriorating items with time proportional demand. Journal of the Operational Research Society, 32(1) 137–142.
Dye, C.Y. and Hsieh, T.P. (2012). An optimal replenishment policy for deteriorating items with effective investment in Preservation Technology. European Journal of Operational Research, 218(1), 106-112.
Dye, C.Y. (2013). The effect of Preservation Technology investment on a non- instantaneous deteriorating inventory model. Omega, 41(1) 872-880.
Dutta, D. and Kumar, P. (2013). Fuzzy inventory models for deteriorating items with shortages and fully backlogged condition. International Journal of Soft Computing and Engineering, 3(2), 393-398.
Huang, Y.H., Wang, C.C., Huang, C.J. and Dye, C.Y. (2011). Comments on preservation technology investment for deteriorating inventory. African Journal of Business Management., 5(11) 4636-4643.
Hsieh, T.P. and Dye, C.Y. (2013). A production inventory model incorporating the effect of preservation technology investment when demand is fluctuating with time. Journal of Computational and Applied Mathematics, 239, 25-36.
Johnny, C.H., Adriano, O.S. and Chang, Y.L. (2007). An evaluation of lot-sizing heuristics for deteriorating inventory in material requirements planning systems. Computers and Operations Research, 34(9) 2562–2575.
Kang, S. and Kim, I. (1983). A study on the price and production level of the deteriorating inventory system. International Journal of Production Research, 21(6) 449–460.
Lin, D.C. and Yao, J.S. (2000). Fuzzy economic production for production inventory. Fuzzy Sets and Systems, 111(1) 465-495.
Murr, D.P. and Morris, L.L. (1975). Effect of storage temperature on post change in mushrooms. Journal of the American Society for Horticultural Science, 100(1) 16–19.
Ouyang, L.Y., Wu, K.S. and Yang, C.T. (2006). A study on an inventory model for non- instantaneous deteriorating items with permissible delay in payments. Computers and Industrial Engineering, 51(4) 637–651.
Papachristos, S. and Skouri, K. (2000). An optimal replenishment policy for deteriorating items with time-varying demand and partial-exponential type-backlogging. Operations Research Letters, 27(4) 175-184.
Ruoning, X. and Xiaoyan, Z. (2010). Analysis of supply chain coordination under fuzzy demand in a two-stage supply chain. Applied Mathematical Modeling, 34(1) 129-139.
San José, L.A., Sicilia, J. and Garc?a-Laguna, J. (2006). Analysis of an inventory system with exponential partial backordering. International Journal of Production Economics, 100(1) 76–86.
Singh, S.R. and Singh, C. (2008). Fuzzy inventory model for finite rate of replenishment using signed distance method. International Transactions in Mathematical Sciences and Computer, 1(1) 21-30.
Singh, S.R., Kumari, R. and Kumar, N. (2011). Optimization of fuzzy inventory model for differential items. International Journal of Operational Research, 11(3) 290-315.
Singh, C. and Singh, S.R. (2011). Imperfect production process with exponential demand rate, Weibull deterioration under inflation. International Journal of Operational Research, 12(4) 430-445.
Teng, J.T., Yang, H.L. and Ouyang, L.Y. (2003). On an EOQ model for deteriorating items with time-varying demand and partial backlogging. Journal of the Operational Research Society , 54(4) 432-436.
Teng, J.T. and Yang, H.L. (2004). Deterministic economic order quantity models with partial backlogging when demand and cost are fluctuating with time. Journal of the Operational Research Society, 55(5) 495-503.
Urvashi and Singh, S. R. (2013). Inventory Control with fuzzy inflation and volume flexibility under random planning horizon. International Journal of Computer Applications, 76(11), 8-17.
Wee, H.M., Teng, H.M. and Hsu, P.H. (2010). Preservation technology investment for deteriorating inventory. International Journal of Production Economics, 124(2) 388–394.
Yadav, D., Singh, S. R. and Kumari, R. (2013). Retailer’s optimal policy under inflation in fuzzy environment with trade credit. International Journal of Systems Science, 1-9.
Yang, P.C. and Wee, H.M. (2006). A collaborative inventory system with permissible delay in payment for deteriorating items. Mathematical and Computer Modeling, 43(3-4) 209–221.
Chang, S.C., Yao, J.S. and Lee, H.M. (1998). Economic reorder point for fuzzy backorder quantity. European Journal of Operational Research, 109(1) 183-202.
Chang, H.J. and Lin, W.F. (2010). A partial backlogging inventory model for non-instantaneous deteriorating items with stock-dependent consumption rate under inflation. Yugoslav Journal of Operation Research, 20(1) 35-54.
Chang, C.T., Teng, J.T. and Goyal, S.K. (2010). Optimal replenishment policies for non- instantaneous deteriorating items with stock-dependent demand. International Journal of Production Economics, 123(1) 62–68.
Covert, R.P. and Philip, G.C. (1973). An EOQ model for items with Weibull distribution deterioration. AIIE Transaction, 5(4) 323–326.
Ghare, P.M. and Schrader, G.F. (1963). A model for exponential decaying inventory. Journal of Industrial Engineering, 14(6) 238–43.
Goyal, S.K. and Giri, B.C. (2001). Recent Trends in Modeling of Deteriorating Inventory. European Journal of Operational Research, 134(1) 1–16.
Dave, U. and Patel, L.K. (1981). (T, Si) policy inventory model for deteriorating items with time proportional demand. Journal of the Operational Research Society, 32(1) 137–142.
Dye, C.Y. and Hsieh, T.P. (2012). An optimal replenishment policy for deteriorating items with effective investment in Preservation Technology. European Journal of Operational Research, 218(1), 106-112.
Dye, C.Y. (2013). The effect of Preservation Technology investment on a non- instantaneous deteriorating inventory model. Omega, 41(1) 872-880.
Dutta, D. and Kumar, P. (2013). Fuzzy inventory models for deteriorating items with shortages and fully backlogged condition. International Journal of Soft Computing and Engineering, 3(2), 393-398.
Huang, Y.H., Wang, C.C., Huang, C.J. and Dye, C.Y. (2011). Comments on preservation technology investment for deteriorating inventory. African Journal of Business Management., 5(11) 4636-4643.
Hsieh, T.P. and Dye, C.Y. (2013). A production inventory model incorporating the effect of preservation technology investment when demand is fluctuating with time. Journal of Computational and Applied Mathematics, 239, 25-36.
Johnny, C.H., Adriano, O.S. and Chang, Y.L. (2007). An evaluation of lot-sizing heuristics for deteriorating inventory in material requirements planning systems. Computers and Operations Research, 34(9) 2562–2575.
Kang, S. and Kim, I. (1983). A study on the price and production level of the deteriorating inventory system. International Journal of Production Research, 21(6) 449–460.
Lin, D.C. and Yao, J.S. (2000). Fuzzy economic production for production inventory. Fuzzy Sets and Systems, 111(1) 465-495.
Murr, D.P. and Morris, L.L. (1975). Effect of storage temperature on post change in mushrooms. Journal of the American Society for Horticultural Science, 100(1) 16–19.
Ouyang, L.Y., Wu, K.S. and Yang, C.T. (2006). A study on an inventory model for non- instantaneous deteriorating items with permissible delay in payments. Computers and Industrial Engineering, 51(4) 637–651.
Papachristos, S. and Skouri, K. (2000). An optimal replenishment policy for deteriorating items with time-varying demand and partial-exponential type-backlogging. Operations Research Letters, 27(4) 175-184.
Ruoning, X. and Xiaoyan, Z. (2010). Analysis of supply chain coordination under fuzzy demand in a two-stage supply chain. Applied Mathematical Modeling, 34(1) 129-139.
San José, L.A., Sicilia, J. and Garc?a-Laguna, J. (2006). Analysis of an inventory system with exponential partial backordering. International Journal of Production Economics, 100(1) 76–86.
Singh, S.R. and Singh, C. (2008). Fuzzy inventory model for finite rate of replenishment using signed distance method. International Transactions in Mathematical Sciences and Computer, 1(1) 21-30.
Singh, S.R., Kumari, R. and Kumar, N. (2011). Optimization of fuzzy inventory model for differential items. International Journal of Operational Research, 11(3) 290-315.
Singh, C. and Singh, S.R. (2011). Imperfect production process with exponential demand rate, Weibull deterioration under inflation. International Journal of Operational Research, 12(4) 430-445.
Teng, J.T., Yang, H.L. and Ouyang, L.Y. (2003). On an EOQ model for deteriorating items with time-varying demand and partial backlogging. Journal of the Operational Research Society , 54(4) 432-436.
Teng, J.T. and Yang, H.L. (2004). Deterministic economic order quantity models with partial backlogging when demand and cost are fluctuating with time. Journal of the Operational Research Society, 55(5) 495-503.
Urvashi and Singh, S. R. (2013). Inventory Control with fuzzy inflation and volume flexibility under random planning horizon. International Journal of Computer Applications, 76(11), 8-17.
Wee, H.M., Teng, H.M. and Hsu, P.H. (2010). Preservation technology investment for deteriorating inventory. International Journal of Production Economics, 124(2) 388–394.
Yadav, D., Singh, S. R. and Kumari, R. (2013). Retailer’s optimal policy under inflation in fuzzy environment with trade credit. International Journal of Systems Science, 1-9.
Yang, P.C. and Wee, H.M. (2006). A collaborative inventory system with permissible delay in payment for deteriorating items. Mathematical and Computer Modeling, 43(3-4) 209–221.