Open Access
Issue
RAIRO-Oper. Res.
Volume 55, Number 5, September-October 2021
Page(s) 3141 - 3152
DOI https://doi.org/10.1051/ro/2021063
Published online 21 October 2021
  • S. Bruckner, A. Albrecht, B. Petersen and J. Kreyenschmidt, A predictive shelf life model as a tool for the improvement of quality management in pork and poultry chains. Food Control 29 (2013) 451–460. [Google Scholar]
  • L.E. Cárdenas-Barrón and S.S. Sana, Multi-item EOQ inventory model in a two-layer supply chain while demand varies with a promotional effort. Appl. Math. Model. 39 (2015) 6725–6737. [Google Scholar]
  • B.R. Chowdhury, R. Chakraborty and U.R. Chaudhuri, The validity of modified Gompertz and Logistic models in predicting cell growth of Pediococcus Acidilactici H during the production of bacteriocin pediocin AcH. J. Food Eng. 80 (2007) 1171–1175. [Google Scholar]
  • B.K. Dey, B. Sarkar and M. Sarkar and S. Pareek, An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment, RAIRO: OR 53, 2019 39–57. [Google Scholar]
  • T.J. Fang, Q.K. Wei, C.W. Liao, M.J. Hung and T.H. Wang, Microbiological quality of 18 °Cready-to-eat food products sold in Taiwan. Int. J. Food Microbiol. 80 (2003) 241–250. [Google Scholar]
  • A.M. Gibson, N. Bratchell and T.A. Roberts, The effect of sodium chloride and temperature on rate and extent of growth of clostridium botulinum type an unpasteurized pork slurry. J. Appl. Bacteriol. 62 (1987) 479–490. [Google Scholar]
  • J.W. Grievink, L. Josten and C. Valk, State of the art in food: The changing face of the worldwide food industry. Elsevier Business Information (2002) 663. [Google Scholar]
  • A. Herbon, E. Levner and T.C.E. Cheng, Perishable inventory management with dynamic pricing using time-temperature indicators linked to automatic detecting devices. Int. J. Prod. Econ. 147 (2014) 605–613. [Google Scholar]
  • M.W. Iqbal and B. Sarkar, Recycling of lifetime dependent deteriorated products through different supply chains. RAIRO: OR 53 (2019) 129–156. [Google Scholar]
  • D.H. Jang and K.T. Lee, Quality changes of ready-to-eat ginseng chicken porridge during storage at 25 C. Meat Sci. 92 (2012) 469–473. [Google Scholar]
  • J. Jemai, B.D. Chung and B. Sarkar, Environmental effect for a complex green supply-chain management to control waste: a sustainable approach. J. Clean. Prod. 277 (2020) 122919. [Google Scholar]
  • M.A.A. Khan, A.A. Shaikh, G. Panda, I. Konstantaras and L.E. Cárdenas-Barrón, The effect of advance payment with discount facility on supply decisions of deteriorating products whose demand is both price and stock dependent. Int. Trans. Oper. Res. 27 (2020) 1343–1367. [Google Scholar]
  • R.H. Linton, W.H. Carter, M.D. Pierson and C.R. Hackney, Use of a modified Gompertz equation to model nonlinear survival curves for Listeria Monocytogenes Scott A. J. Food Prot. 58 (1995) 946–954. [Google Scholar]
  • A.S. Mahapatra, B. Sarkar, M.S. Mahapatra, H.N. Soni and S.K. Mazumder, Development of a fuzzy economic order quantity model of deteriorating items with promotional effort and learning in fuzziness with a finite time horizon. Inventions 4 (2019) 36. [Google Scholar]
  • A. Mukherjee and G.C. Mahata, Optimal replenishment and credit policy in an inventory model for deteriorating items under two-levels of trade credit policy when demand depends on both time and credit period involving default risk. RAIRO: OR 52 (2018) 1175–1200. [Google Scholar]
  • S. Mukhopadyay, R.N. Mukherjee and K.S. Chaudhuri, Joint pricing and ordering policy for a deteriorating inventory. Comput. Ind. Eng. 47 (2004) 339–349. [Google Scholar]
  • Y. Qin, J. Wang and C. Wei, Joint pricing and inventory control for fresh produce and foods with quality and physical quantity deteriorating simultaneously. Int. J. Prod. Econ. 152 (2014) 42–48. [Google Scholar]
  • M. Rabbani, N.P. Zia and H. Rafiei, Coordinated replenishment and marketing policies for non-instantaneous stock deterioration problems. Comput. Ind. Eng. 88 (2015) 49–62. [Google Scholar]
  • M. Rabbani, N.P. Zia and H. Rafiei, Joint optimal inventory, dynamic pricing, and advertisement policies for non-instantaneous deteriorating items. RAIRO: OR 51 (2017) 1251–1267. [Google Scholar]
  • B. Sarkar, B.K. Sett and G. Roy, Flexible setup cost and deterioration of products in a supply chain model. Int. J. Appl. Comput. Math. 2 (2016) 25–40. [Google Scholar]
  • B. Sarkar, B.K. Dey, M. Sarkar, S. Hur, B. Mandal and V. Dhaka, Optimal replenishment decision for retailers with variable demand for deteriorating products under a trade-credit policy. RAIRO Oper. Res. 54 (2020) 1685–1701. [Google Scholar]
  • B. Sarkar, M. Sarkar, B. Ganguly and L.E. Cárdenas-Barrón, Combined effects of carbon emission and production quality improvement for fixed lifetime products in a sustainable supply chain management. Int. J. Prod. Econ. 231 (2021) 107867. [Google Scholar]
  • N. Saxena, B. Sarkar and S.R. Singh, Selection of remanufacturing/production cycles with an alternative market: a perspective on waste management. J. Clean. Prod. 245 (2020) 118935. [Google Scholar]
  • N.H. Shah and U.B. Chaudhari, Optimal policies for three players with fixed life time and two-level trade credit for time and credit dependent demand. Adv. Ind. Eng. Manage. 4 (2015) 89–100. [Google Scholar]
  • N.H. Shah and M.Y. Jani, Optimal ordering for deteriorating items of fixed-life with quadratic demand and two-level trade credit. In: Optimal Inventory Control and Management Techniques. IGI Global (2016) 1–16. [Google Scholar]
  • N.H. Shah and M.Y. Jani, Economic order quantity model for non-instantaneously deteriorating items under order-size-dependent trade credit for price-sensitive quadratic demand. AMSE J. 37 (2016) 1–19. [Google Scholar]
  • N.H. Shah, M.Y. Jani and D.B. Shah, Economic order quantity model under trade credit and customer returns for price-sensitive quadratic demand. Rev. Invest. Oper. 36 (2015) 240–248. [Google Scholar]
  • N.H. Shah, U.B. Chaudhari and M.Y. Jani, Optimal down-stream credit period and replenishment time for deteriorating inventory in a supply chain. J. Basic Appl. Res. Int. 14 (2015) 101–115. [Google Scholar]
  • N.H. Shah, M.Y. Jani and U.B. Chaudhari, Impact of future price increase on ordering policies for deteriorating items under quadratic demand. Int. J. Ind. Eng. Comput. 7 (2016) 423–436. [Google Scholar]
  • N.H. Shah, U. Chaudhari and L.E. Cárdenas-Barrón, Integrating credit and replenishment policies for deteriorating items under quadratic demand in a three echelon supply chain. Int. J. Syst. Sci. Oper. Logist. 7 (2020) 34–45. [Google Scholar]
  • A.A. Shaikh, L.E. Cárdenas-Barrón, A.K. Bhunia and S. Tiwari, An inventory model of a three-parameter Weibull distributed deteriorating item with variable demand dependent on price and frequency of advertisement under trade credit. RAIRO: OR 53 (2019) 903–916. [Google Scholar]
  • A.A. Shaikh, L.E. Cárdenas-Barrón and S. Tiwari, A two-warehouse inventory model for non-instantaneous deteriorating items with interval valued inventory costs and stock dependent demand under inflationary conditions. Neural Comput. App. 31 (2019) 1931–1948. [Google Scholar]
  • E. Stavropoulou and E. Bezirtzoglou, Predictive modeling of microbial behavior in food. Foods 8 (2019) 654. [Google Scholar]
  • A. Taleizadeh and M. Nematollahi, An inventory control problem for deteriorating items with back-ordering and financial considerations. Appl. Math. Model. 38 (2014) 93–109. [Google Scholar]
  • J. Wang, J. Chen, Y. Hu, H. Hu, G. Liu and R. Yan, Application of a predictive growth model of pseudomonas spp. for estimating shelf life of fresh Agaricus bisporus. J. Food Prot. 80 (2017) 1676–1681. [Google Scholar]
  • R.C. Whiting and R.L. Buchanan, A classification of models in predictive microbiology. Food Microbiol. 10 (1993) 175–177. [Google Scholar]
  • M.F. Yang and W.C. Tseng, Deteriorating inventory model for chilled food. Math. Prob. Eng. 2015 (2015) 816876. [Google Scholar]
  • J. Zhang, G. Liu, Q. Zhang and Z. Bai, Coordinating a supply chain for deteriorating items with a revenue sharing and cooperative investment contract. Omega 56 (2015) 37–49. [Google Scholar]
  • L.C. Iao, H.I. Hsiao and M.F. Yang, Temperature monitoring for quality prediction and inventory control in cold chain: A case of 18 °Cready-to-eat food in Taiwan. 7 th International European Forum (Igls-Forum) on System Dynamics and Innovation in Food Networks, Innsbruck, Austria (2013) 593–600. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.