EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 511 (2024) E3S Web Conf., 511 (2024) 01005 References
Open Access
Issue
E3S Web Conf.
Volume 511, 2024
International Conference on “Advanced Materials for Green Chemistry and Sustainable Environment” (AMGSE-2024)
Article Number 01005
Number of page(s) 13
DOI https://doi.org/10.1051/e3sconf/202451101005
Published online 10 April 2024
  1. Yum, B.J., McDowell, E.D., Optimal Inspection Policies in a Serial Production System including scrap, rework and repair’, An MILP approach. Int. J. Prod. Res, Vol. 25, No.10, pp. 1451–1464 (1987). [CrossRef] [Google Scholar]
  2. Agnihothri, S.R., Kenett, R.S., Impact of defects on a process with rework, Eur. J. Oper. Res, Vol. 80, No. 2, pp. 308–327, (1995). [CrossRef] [Google Scholar]
  3. Chung, K.J., Bounds for production lot sizing with machine breakdowns, Compute. Ind. Eng., Vol. 32 (1), pp. 139–144, (1997). [CrossRef] [Google Scholar]
  4. Jamal, A.M.M., Sarker, B.R., Mondal, S., Optimal manufacturing batch size with rework process at a single-stage, production system Compute Ind. Eng., Vol. 47, No.1, pp. 77–89, (2004). [CrossRef] [Google Scholar]
  5. Chiu, S.W., Chiu, Y.S.P., Mathematical modelling for production system with backlogging and failure in repair, J. Sci. Ind. Res., Vol. 65, No. 6, pp. 499–506, (2006). [Google Scholar]
  6. Islam, S., Roy, T.K., A fuzzy EPQ model with flexibility and reliability consideration and demand dependent unit production cost under a space constraint: a fuzzy geometric programming approach, Appl. Math. Compute., Vol. 176, No. 2, pp. 531–544, (2006). [Google Scholar]
  7. Chiu, S.W., Wang, S.L., Chiu, Y.S.P., Determining the optimal run time for EPQ model with scrap, rework, and stochastic breakdowns, Eur. J. Oper. Res., Vol. 180, No. 2, pp. 664–676, (2007). [CrossRef] [Google Scholar]
  8. Haji, B., Haji, A., RahmatiTavakol, A., Scheduling accumulated rework in a normal cycle: optimal batch production with minimum rework cycles’, J. Ind. Syst. Eng., Vol. 2, No.2, pp. 236–249, 2008. [Google Scholar]
  9. Haji B., Haji A., Haji R., Optimal batch production with minimum rework cycles and constraint on accumulated defective units, Service Operations, Logistics and Informatics, SOLI ’09. In: IEEE/INFORMS International Conference, pp. 633–638, (2009). [Google Scholar]
  10. Cárdenas-Barrón, L.E., Economic production quantity with rework process at a singlestage manufacturing system with planned backorders, ComputingEng. J., Vol. 57, No. 3, pp. 1105–1113, (2009). [Google Scholar]
  11. Taleizadeh, A.A., Najafi, A.A., Niaki, S.T.A., Economic production quantity model with scraped items and limited production capacity’, Sci. Iran, Vol. 17, No. 1, pp. 58–69, (2010). [Google Scholar]
  12. Chakraborty, T., Giri, B.C., ‘Joint determination of optimal safety stocks and production policy for an imperfect production system, Appl. Math. Model. 36 (2), 712–722, (2012). [CrossRef] [Google Scholar]
  13. Jaggi, C.K., Goel, S.K. and Mittal, M., Credit financing in economic ordering policies for defective items with allowable shortages, Applied Mathematics and Computation, Vol. 210, No. 10, pp. 5268–5282, (2013). [CrossRef] [Google Scholar]
  14. Pal, B., Sana, S.S. and Chaudhuri, K., Maximizing profits for an EPQ model with unreliable machine and rework of random defective items, International Journal of Systems Science, Vol. 44, No. 3, pp. 582–594, (2013). [CrossRef] [Google Scholar]
  15. Krishnamoorthi, C. and Panayappan, S., An EPQ model for an imperfect production system with rework and shortages’, International Journal of Operation Research, Vol. 17, No. 1, pp. 104–124, (2013). [CrossRef] [Google Scholar]
  16. Wahab, M., Mamun, S., Ongkunaruk, P. EOQ models for a coordinated two-level international supply chain considering imperfect items and environmental impact. Int. J. Prod. Econ., Vol. 134, No. 1, pp. 151–158, (2011). [CrossRef] [Google Scholar]
  17. Zhang, B., Xu, L., Multi-item production planning with carbon cap and trade mechanism. Int. J. Prod. Econ., Vol. 144, No. 1, pp. 118–127, (2013). [CrossRef] [Google Scholar]
  18. Hovelaque, V., Bironneau, L., The carbon-constrained EOQ model with carbon emission dependent demand. Int. J. Prod. Econ., Vol. 164, pp. 285–291, (2015). [CrossRef] [Google Scholar]
  19. Hammami, R., Nouira, I., Frein, Y.,. Carbon emissions in a multi-echelon productioninventory model with lead time constraints. Int. J. Prod. Econ., Vol. 164, pp. 292–307, (2015). [CrossRef] [Google Scholar]
  20. Tiwari, S., Daryanto, Y., Wee, H.M. Sustainable inventory management with deteriorating and imperfect quality items considering carbon emission. J. Clean. Prod., Vol. 192, pp. 281–292, (2018). [CrossRef] [Google Scholar]
  21. Taleizadeh, A.A., Soleymanfar, V.R., Govindan, K., Sustainable economic production quantity models for inventory systems with shortage. J. Clean. Prod., Vol. 174, pp. 1011–1020, (2018). [CrossRef] [Google Scholar]
  22. Sazvar, Z., Rahmani, M., Govindan, K. A sustainable supply chain for organic, conventional agro-food products: the role of demand substitution, climate change and public health. J. Clean. Prod., Vol. 194, pp. 564–583, (2018). [CrossRef] [Google Scholar]
  23. Daryanto, Y., Wee, H.M., Astanti, R.D. Three-echelon supply chain model considering carbon emission and item deterioration. Transport. Res. E Logist. Transport. Rev., Vol. 122, pp. 368–383, (2019). [CrossRef] [Google Scholar]
  24. Wu, K. and Yao, J., Production, manufacturing and logistics fuzzy inventory with 690 backorder for fuzzy order quantity and fuzzy shortage quantity, European Journal of Operational Research, Vol. 150, pp. 320–352, (2003). [CrossRef] [Google Scholar]
  25. Kao, C. and Hsu, W. K., A single period inventory model with fuzzy demand’, Computers and Mathematics with Applications, Vol. 43, pp. 841–848, (2002). [CrossRef] [Google Scholar]
  26. Dutta, P., Chakraborty, D. and Roy, A. R., A single period inventory model with fuzzy random variable demand’, Mathematical and Computer Modelling, Vol. 41, pp. 91–92, (2005). [Google Scholar]
  27. Yao, J. and Chiang, J., Inventory without backorder with fuzzy total cost and fuzzy storing cost defuzzified by centroid and signed distance, European Journal of Operational Research, Vol. 148, pp. 401–409, 2003. [CrossRef] [Google Scholar]
  28. Syed, J. K. and Aziz, L. A., Fuzzy inventory model without shortages using signed distance method’, Applied Mathematics & Information Sciences an International Journal, Vol. 1, No. 2, pp. 203–209, (2007). [Google Scholar]
  29. Wang, X., Tang, W. and Zhao, R., Fuzzy economic order quantity models without backordering’, Tsinghua Science and Technology, Vol. 12, No.1, pp. 91–96, (2007). [CrossRef] [Google Scholar]
  30. Vijayan, T. and Kumaran, M., Inventory models with a mixture of backorders and lost sales under fuzzy cost, European Journal of Operational Research, Vol. 189, pp. 105–119, (2008). [CrossRef] [Google Scholar]
  31. Chou, C., Fuzzy economic order quantity inventory model, International Journal of Innovative Computing, Information and Control, Vol. 5, No. 9, pp. 2585–2592, (2009). [Google Scholar]
  32. Mahata, G. C. and Goswami, A., An EOQ model with fuzzy lead time, fuzzy demand and fuzzy cost coefficients, International Journal of Engineering and Applied Sciences, Vol. 5, No. 5, pp. 295–302, (2009). [Google Scholar]
  33. Jadhav, O. S. and Bodkhe, S. G., Multi-objective fuzzy inventory model of deteriorating items: without shortages’, International Journal of Mathematics Research, Vol. 2, No. 3, pp. 185–196, (2010). [Google Scholar]
  34. Sayal, A., Singh, A.P., Aggarwal, D.,. Inventory model in fuzzy environment without shortage using triangular fuzzy number with sensitivity analysis, Int. J. Agricult. Stat. Sci., vol. 14, No. 1, pp. 391–396, (2018). [Google Scholar]
  35. Rajput, N., Chauhan, A., Pandey, R.K., Singh, A.P. An optimization of fuzzy EOQ model in healthcare industries with three different demand pattern using signed distance technique. Mathematics in Engineering, Science and Aerospace, vol. 10, No. 2, pp. 205–2. (2020). [Google Scholar]
  36. Singh, A.P., Chauhan, A., Chauhan, D., Patel, D., Dhiman, N.,. A comprehensive study of fuzzy economic quantity model with ramp type demand for perishable products, AIP Conference Proceedings, Vol. 2481, No. 1, pp. 040039, (2022). [CrossRef] [Google Scholar]
  37. Sayal, A., Singh, A.P., Chauhan, A., Dhiman, N.,. Optimization of economic order quantity model with shortages having two parameter Weibull demand and deterioration rate under crisp and fuzzy system, AIP Conference Proceedings, Vol. 2481, No. 1, pp. 040031, (2022). [CrossRef] [Google Scholar]
  38. Sayal, A., Singh, A.P., Chauhan, A., Dhiman, N., Optimized crisp and fuzzy inventory system of deteriorating items with partial backlogging under the effect of inflation, AIP Conference Proceedings, Vol. 2481, No. 1, pp. 040029, (2022). [CrossRef] [Google Scholar]
  39. Sayal, A., Singh, A.P., Chauhan, A., Dhiman, N., Optimization of inventory model for deteriorating items with time varying holding cost under uncertainty, AIP Conference Proceedings, Vol. 2481, No. 1, pp. 040030, (2022). [CrossRef] [Google Scholar]
  40. Arora, R., Singh, A.P., Sharma, R., Chauhan, A. A remanufacturing inventory model to control the carbon emission using cap-and-trade regulation with the hexagonal fuzzy number, Benchmarking: An International Journal, Vol. 29, No. 7, pp. 2202–2230, (2022). [CrossRef] [Google Scholar]
  41. Sharma, R., Singh, A.P., Arora, R., Chauhan, A Effect of uncertainty in demand and production for manufacturing industries during COVID-19, International Journal of Services and Operations Management, Vol. 43, No. 3, pp. 378–400, (2022). [CrossRef] [Google Scholar]
  42. Singh, A.P., Sharma, R., Arora, R., Chauhan, A., Optimization of an inventory model for conclusive and inconclusive cost parameters using triangular and trapezoidal fuzzy number, International Journal of Mathematics in Operational Research, Vol. 21, No. 4, pp. 529–553, (2022). [CrossRef] [Google Scholar]
  43. Singh, A.P., Sahedev, Bhandari, S., Chauhan, A., Fuzzy optimisation for economic ordered quantity model with stock-dependent demand and nonlinear holding cost, International Journal of procurement management, (2023) Doi: 10.1504/IJPM.2023.10059228 [Google Scholar]
  44. Poswal P., Chauhan A, Aarya DD., Boadh R., Rajoria Y.K., Gaiola S.U Optimal strategy for remanufacturing system of sustainable products with trade credit under uncertain scenario, Materials Today: Proceedings, 69(2), 165–173, (2022a). https://doi.org/10.1016/j.matpr.2022.08.303 [CrossRef] [Google Scholar]
  45. Poswal P, Chauhan A, Rajoria Y.K, Boadh R, Goel A: Fuzzy optimization model of two parameter weibull deteriorating rate with quadratic demand and variable holding cost under allowable shortages, in Yugoslav Journal of Operations Research, 32(4):453–479, (2022b). DOI: https://doi.org/10.2298/YJOR220115021P [CrossRef] [Google Scholar]
  46. Poswal, P., Chauhan, A., Boadh, R., and Rajoria, Y.K.: A Review on Fuzzy EOQ Model under shortage, ICAES-2021, published in AIP Conference Proceeding, 2481, 040023 (2022c); https://doi.org/10.1063/5.0103757 [CrossRef] [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.