An evaluation of inventory systems via an evidence theory for deteriorating items under uncertain conditions and advanced payment

Document Type : Article

Authors

1 Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

2 Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Ira

3 Department of Industrial Engineering and Management Systems, Amirkabir University, Tehran, Iran.

Abstract

The inventory model for deteriorating items, which is developed by The Evidential Reasoning Algorithm (ERA) and the imprecise inventory costs, is one of the most important factors in complex systems which plays a vital role in Payment. The ERA is able to strengthen the precision of the model and give the perfect interval-valued utility. In this model, during lead-time and reorder level two different cases can be happened which the mathematical model turns into an imposed nonlinear mixed integer problem with interval objective for each case. Placement of an order, which is overlooked by many researchers till now, is normally connected with the advance payment (AP) in business. Specifying the optimal profit and the optimal number of cycles in the finite time horizon and lot-sizing in each cycle, are our goals so. In order to solve this model, we apply the real-coded genetic algorithm (RCGA) with ranking selection. By the model, we represent some numerical examples and also a sensitivity analysis with the variation of different inventory parameters.

Keywords

Main Subjects


  1. References:

    1. Gupta, R.K., Bhunia, A.K., and Goyal, S.K. An application of genetic algorithm in solving an inventory model with advance payment and interval valued inventory costs", Mathematical and Computer Modeling, 49(5{6), pp. 893{905 (2009).
    2. Wu, J., Skouri, K., Teng, J.T., and Hu, Y. Two inventory systems with trapezoidal-type demand rate and time-dependent deterioration and backlogging", Expert Systems with Applications, 46, pp. 367{379 (2016).
    3. Teng, J., Cardenas-Barron, L.E., Chang, H., Wu. J., and Hu, Y. Inventory lot-size policies for deteriorating items with expiration dates and advance payments", Applied Mathematical Modelling, 40, pp. 8605{8616 (2016).
    4. Jaggi, C.K., Tiwari, S., and Sha_, A. E_ect of deterioration on two-warehouse inventory model with imperfect quality", Computers & Industrial Engineering, 88, pp. 378{385 (2015).
    5. Widyadana, G.A. and Irohara, T. Modelling multi tour inventory routing problem for deteriorating items with time windows", International Journal of Science and Technology, pp. 932{941 (2019).
    6. Li, Ruihai, Skouri, K., Teng, J.T., and Yang, W.G. Seller's optimal replenishment policy and payment term among advance, cash, and credit payments", International Journal of Production Economics, Elsevier, 197(C), pp. 35{42 (2018).
    7. Feng, L., Chan, Y.L., and C_ardenas-Barr_on, L.E. Pricing and lot-sizing polices for perishable goods when the demand depends on selling price, displayed stocks, and expiration date", International Journal of Production Economics, 185, pp. 11{20 (2017).
    8. Chih-Te Yang, Cha-Huei Ho, Hsiu-Mei Lee and Liang- Yuh Ouyang. Supplier-retailer production and inventory models with defective items and inspection errors in non-cooperative and cooperative environments", RAIRO Operations Research, 52(2), pp. 453{ 471 (2018). 9. Maiti, A.A., Maiti, M.K., and Maiti, M. Inventory model with stochastic lead-time and price dependent demand incorporating advance payment", Applied Mathematical Modelling, 33(5), pp. 2433{2443 (2009). 10. Taleizadeh, A.A. An EOQ model with partial backordering and advance payments for an evaporating item", International Journal of Production Economics, 155, pp. 185{193 (2014). 11. Nodoust, S., Mirzazadeh, A., and Mohammadi, M. A genetic algorithm for an inventory system under belief structure inationary condition", RAIRO Operations Research, 50, pp. 1027{1041 (2016). 12. Tiwari, S., Jaggi, C.K., Gupta, M., and C_ardenas- Barr_on, L.E. Optimal pricing and lot-sizing policy for supply chain system with deteriorating items under limited storage capacity", International Journal of Production Economics, 200, pp. 278{290 (2018). 13. Zhang, Q., Tsao, Y.C., and Chen, T.H. Economic order quantity under advance payment", Applied Mathematical Modelling, 38(24), pp. 5910{5921 (2014). 14. Taleizadeh, A.A., Soleymanfar, V.R., and Govindan, K. Sustainable economic production quantity models for inventory systems with shortage", Journal of Cleaner Production, 174, pp. 1011{1020 (2018). 15. Tiwari, S., C_ardenas-Barr_on, L.E., Khanna, A., and Jaggi, C.K. Impact of trade credit and ination on retailer's ordering policies for non-instantaneous deteriorating items in a two-warehouse environment", International Journal of Production Economics, 176, pp. 154{169 (2016). 16. Pourmohammad zia, N. and Taleizadeh, A.A. A lotsizing model with backordering under hybrid linkedto- order multiple advance payments and delayed payment", Transportation Research Part E: Logistics and Transportation Review, 82, pp. 19{37 (2015). 17. Maiti, A.K., Bhunia, A.K., and Maiti, M. Some inventory problems via genetic algorithms", Ph.D. Thesis, Department of Mathematics. Vidyasagar University, India (2007). 18. Elhafsi, M. and Hamouda, E. Managing an integrated production and inventory system selling to a dual market: Long-term and walk-in", European Journal of Operational Research, 268(1), pp. 215{230 (2018). 19. Dempster, A.P. Upper and lower probabilities induced by a multi valued mapping", The Annals of Mathematical Statistics, 38(2), pp. 325{339 (1967). 20. Glenn, Sh., A Mathematical Theory of Evidence, Princeton University Press, ISBN 0-608-02508-9 (1976). 21. Kari, S., and Ferson, S., Combination of evidence in dempster-shafer theory, Sandia National Laboratories SAND, 0835 (2002). 22. Park, Y.B., Yoo, J.S., and Park, H.S. A genetic algorithm for the vendor-managed inventory routing problem with lost sales", Expert Systems with Applications, 53, pp. 149{159 (2016). M. Soleimani Amiri et al./Scientia Iranica, Transactions E: Industrial Engineering 27 (2020) 3338{3351 3351 23. Hiassat, A., Diabat, A., and Rahwan, L. A genetic algorithm approach for location-inventory-routing problem with perishable products", Journal of Manufacturing Systems, 42, pp. 93{103 (2017). 24. Azadeh, A., Elahi, S., Hosseinabadi Farahani, M., and Nasirian, B. A genetic algorithm-Taguchi based approach to inventory routing problem of a single perishable product with transshipment", Computers & Industrial Engineering, 104, pp. 124{133 (2017). 25. Taleizadeh, A.A., Akhavan Niaki, S.T., Aryanezhad, M.B., and Sha_i, N. A hybrid method of fuzzy simulation and genetic algorithm to optimize constrained inventory control systems with stochastic replenishments and fuzzy demand", Information Sciences, 220, pp. 425{441 (2013). 26. Saracoglu, I., Topaloglu, S., and Keshkinturk, T. A genetic algorithm approach for multi-product multiperiod continuous review inventory models", Expert Systems with Applications, 41(18), pp. 8189{8202 (2014). 27. O'Neill, B. and Sanni, S. Pro_t optimisation for deterministic inventory systems with linear cost", Computers & Industrial Engineering, 122, pp. 303{ 317 (2018). 28. Souri M.E., Sheikh, R., and Sanad, Sh.S. Grey SERVQUAL method to measure consumers' attitudes towards green products - A case study of Iranian consumers of LED bulbs", Journal of Cleaner Production, 177, pp. 187{196 (2018). 29. Ishibuchi, H. and Tanaka, H. Multi objective programming in optimization of the interval objective function", European Journal of Operational Research, 48, pp. 219{225 (1990). 30. Chanas, S. and Kutcha, D. Multiobjective, programming in the optimization of interval objective functions - A generalized approach", European Journal of Operational Research, 94(3), pp. 594{598 (1996). 31. Sengupta, A. and Pal, T.K. Theory and methodology on comparing interval numbers", European Journal of Operational Research, 127, pp. 28{43 (2000). 32. Mahato, S.K. and Bhunia, A.K. Interval-arithmeticoriented interval computing technique for global optimization", Applied Mathematics Research Express, 2006, p. 69642 (2006). 33. Gupta, R.K, Bhunia, A.K., and Goyal, S.K. An application of genetic algorithm in a marketing oriented inventory model with interval valued inventory costs and three-component demand rate dependent on displayed stock level", Applied Mathematics and Computation, 192(2), pp. 466{478 (2007). 34. Ahmadzadeh, F. Multi criteria decision making with evidential reasoning under uncertainty", 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (2016). 35. Gupta, R.K., Bhunia, A.K., and Roy, D. A GA based penalty function technique for solving constrained redundancy allocation problem of series system with interval valued reliability of components", Journal of Computational and Applied Mathematics, 232(2), pp. 275{284 (2009). 36. Sahoo, L., Bhunia, A.K., and Kapur, P.K. Genetic algorithm base multi-objective reliability optimization in interval environment", Applied Mathematics and Computation, 62(1), pp. 152{160 (2007).
Volume 27, Issue 6 - Serial Number 6
Transactions on Industrial Engineering (E)
November and December 2020
Pages 3338-3351
  • Receive Date: 05 November 2018
  • Revise Date: 02 March 2019
  • Accept Date: 10 June 2019