How to cite this paper
Jawla, P & Singh, S. (2016). A reverse logistic inventory model for imperfect production process with preservation technology investment under learning and inflationary environment.Uncertain Supply Chain Management, 4(2), 107-122.
Refrences
Badiru, A.B. (1995). Multivariate analysis of the effect of learning and forgetting on product quality. International Journal of Production Research, 33(3), 777–794.
Buzacott, J.A. (1975). Economic order quantities with inflation. Operational Research Quarterly, 26(3), 1188-1191.
Covert, R.P., & Philip, G.C. (1973). An EOQ model with Weibull distribution deterioration. AIIE Transactions, 5(4), 323–326.
Dekker, R., Fleischmann, M., Inderfurth, K., & van Wassenhove, L. N. (Eds.). (2013). Reverse logistics: quantitative models for closed-loop supply chains. Springer Science & Business Media.
Dobos, I., & Richter, K. (2003). A production/recycling model with stationary demand and return rates. Central European Journal of Operations Research, 11(1), 35–46.
Dye, CY., & Hsieh, TP. (2012). An optimal replenishment policy for deteriorating items with effective investment in preservation technology. European Journal of Operational Research, 218(1), 106–112.
Garvin, D.A. (1988). Managing Quality. Free Press, New York.
Ghare, P.M., & Schrader, G.H. (1963). A model for an exponentially decaying inventory. Journal of Industrial Engineering, 14(5), 238–243.
Guide, V. D. R., Jayaraman, V., & Linton, J. D. (2003). Building contingency planning for closed-loop supply chains with product recovery. Journal of operations Management, 21(3), 259-279.
Gupta, R., & Vrat, P. (1986). Inventory model with multi-items under constraint systems for stock dependent consumption rate. Operations Research, 24(1), 41-42.
Jaber, M. Y., & El Saadany, A. M. (2011). An economic production and remanufacturing model with learning effects. International Journal of Production Economics, 131(1), 115-127.
Jaber, M.Y., & Bonney, M. (2003). Lot sizing with learning and forgetting in set-ups and in product quality. International Journal of Production Economics, 83(1), 95–111.
Johnson, M.R., & Wang, M.H. (1998). Economical evaluation of disassembly operations for recycling, remanufacturing and reuse. International Journal of Production Research, 36(12), 3227–3252.
Krumwiede, D. W., & Sheu, C. (2002). A model for reverse logistics entry by third-party providers. Omega, 30(5), 325-333.
Liao, H. C., Tsai, C. H., & Su, C. T. (2000). An inventory model with deteriorating items under inflation when a delay in payment is permissible.International Journal of Production Economics, 63(2), 207-214.
Nahmias, S., & Rivera, H. (1979). A deterministic model for a repairable item inventory system with a finite repair rate. International Journal of Production Research, 17(3), 215–221.
Ouyang, L. Y., Wu, K. S., & Yang, C. T. (2006). A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments. Computers & Industrial Engineering, 51(4), 637-651.
Ray, J., & Chaudhuri, K. S. (1997). An EOQ model with stock-dependent demand, shortage, inflation and time discounting. International Journal of Production Economics, 53(2), 171-180.
Sarkar, B., & Moon, I. (2011). An EPQ model with inflation in an imperfect production system. Applied Mathematics and Computation, 217(13), 6159-6167.
Schrady, D. A. (1967). A deterministic inventory model for reparable items.Naval Research Logistics Quarterly, 14(3), 391-398.
Singh, S. R., Jain, S., & Pareek, S. (2012). A warehouse imperfect fuzzified production model with shortages under inflationary conditions. Advances in Decision Sciences, 2012, Article ID638060, 16 pages.
Singh, S., Jain, S., & Pareek, S. (2013). An imperfect quality items with learning and inflation under two limited storage capacity. International Journal of Industrial Engineering Computations, 4(4), 479-490.
Singh, S., Prasher, L., & Saxena, N. (2013). A centralized reverse channel structure with flexible manufacturing under the stock out situation.International Journal of Industrial Engineering Computations, 4(4), 559-570.
Singh, SR., & Saxena, N. (2012). An Optimal Returned Policy for a Reverse Logistics Inventory Model with Backorders. Advances in Decision Sciences, Article ID 386598: 21 pages.
Wee, H., Hsu, P., & Teng, H. (2010). Preservation technology investment for deteriorating inventory. International Journal of Production Economics, 124(2), 388–394.
Wright, T. (1936). Factors affecting the cost of airplanes. Journal of Aeronautical Science, 3(2), 122–128.
Wu, K.S., Ouyang, L.Y., & Yang, C.T. (2006). An optimal replenishment policy for non- instantaneous deteriorating items with stock-dependent demand and partial backlogging. International Journal of Production Economics, 101(2), 369–384.
Yang, P. C., Chung, S. L., Wee, H. M., Zahara, E., & Peng, C. Y. (2013). Collaboration for a closed-loop deteriorating inventory supply chain with multi-retailer and price-sensitive demand. International Journal of Production Economics, 143(2), 557-566.
Yelle, L.E. (1979). The learning curve: Historical review and comprehensive survey. Decision Sciences, 10(2), 302–328.
Buzacott, J.A. (1975). Economic order quantities with inflation. Operational Research Quarterly, 26(3), 1188-1191.
Covert, R.P., & Philip, G.C. (1973). An EOQ model with Weibull distribution deterioration. AIIE Transactions, 5(4), 323–326.
Dekker, R., Fleischmann, M., Inderfurth, K., & van Wassenhove, L. N. (Eds.). (2013). Reverse logistics: quantitative models for closed-loop supply chains. Springer Science & Business Media.
Dobos, I., & Richter, K. (2003). A production/recycling model with stationary demand and return rates. Central European Journal of Operations Research, 11(1), 35–46.
Dye, CY., & Hsieh, TP. (2012). An optimal replenishment policy for deteriorating items with effective investment in preservation technology. European Journal of Operational Research, 218(1), 106–112.
Garvin, D.A. (1988). Managing Quality. Free Press, New York.
Ghare, P.M., & Schrader, G.H. (1963). A model for an exponentially decaying inventory. Journal of Industrial Engineering, 14(5), 238–243.
Guide, V. D. R., Jayaraman, V., & Linton, J. D. (2003). Building contingency planning for closed-loop supply chains with product recovery. Journal of operations Management, 21(3), 259-279.
Gupta, R., & Vrat, P. (1986). Inventory model with multi-items under constraint systems for stock dependent consumption rate. Operations Research, 24(1), 41-42.
Jaber, M. Y., & El Saadany, A. M. (2011). An economic production and remanufacturing model with learning effects. International Journal of Production Economics, 131(1), 115-127.
Jaber, M.Y., & Bonney, M. (2003). Lot sizing with learning and forgetting in set-ups and in product quality. International Journal of Production Economics, 83(1), 95–111.
Johnson, M.R., & Wang, M.H. (1998). Economical evaluation of disassembly operations for recycling, remanufacturing and reuse. International Journal of Production Research, 36(12), 3227–3252.
Krumwiede, D. W., & Sheu, C. (2002). A model for reverse logistics entry by third-party providers. Omega, 30(5), 325-333.
Liao, H. C., Tsai, C. H., & Su, C. T. (2000). An inventory model with deteriorating items under inflation when a delay in payment is permissible.International Journal of Production Economics, 63(2), 207-214.
Nahmias, S., & Rivera, H. (1979). A deterministic model for a repairable item inventory system with a finite repair rate. International Journal of Production Research, 17(3), 215–221.
Ouyang, L. Y., Wu, K. S., & Yang, C. T. (2006). A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments. Computers & Industrial Engineering, 51(4), 637-651.
Ray, J., & Chaudhuri, K. S. (1997). An EOQ model with stock-dependent demand, shortage, inflation and time discounting. International Journal of Production Economics, 53(2), 171-180.
Sarkar, B., & Moon, I. (2011). An EPQ model with inflation in an imperfect production system. Applied Mathematics and Computation, 217(13), 6159-6167.
Schrady, D. A. (1967). A deterministic inventory model for reparable items.Naval Research Logistics Quarterly, 14(3), 391-398.
Singh, S. R., Jain, S., & Pareek, S. (2012). A warehouse imperfect fuzzified production model with shortages under inflationary conditions. Advances in Decision Sciences, 2012, Article ID638060, 16 pages.
Singh, S., Jain, S., & Pareek, S. (2013). An imperfect quality items with learning and inflation under two limited storage capacity. International Journal of Industrial Engineering Computations, 4(4), 479-490.
Singh, S., Prasher, L., & Saxena, N. (2013). A centralized reverse channel structure with flexible manufacturing under the stock out situation.International Journal of Industrial Engineering Computations, 4(4), 559-570.
Singh, SR., & Saxena, N. (2012). An Optimal Returned Policy for a Reverse Logistics Inventory Model with Backorders. Advances in Decision Sciences, Article ID 386598: 21 pages.
Wee, H., Hsu, P., & Teng, H. (2010). Preservation technology investment for deteriorating inventory. International Journal of Production Economics, 124(2), 388–394.
Wright, T. (1936). Factors affecting the cost of airplanes. Journal of Aeronautical Science, 3(2), 122–128.
Wu, K.S., Ouyang, L.Y., & Yang, C.T. (2006). An optimal replenishment policy for non- instantaneous deteriorating items with stock-dependent demand and partial backlogging. International Journal of Production Economics, 101(2), 369–384.
Yang, P. C., Chung, S. L., Wee, H. M., Zahara, E., & Peng, C. Y. (2013). Collaboration for a closed-loop deteriorating inventory supply chain with multi-retailer and price-sensitive demand. International Journal of Production Economics, 143(2), 557-566.
Yelle, L.E. (1979). The learning curve: Historical review and comprehensive survey. Decision Sciences, 10(2), 302–328.