Although pricing and inventory control are crucial decisions in each production system, these decisions are usually investigated separately. This paper considers pricing and inventory control decisions simultaneously in a hybrid production system. The hybrid production system has two recovery options, remanufacturing and refurbishing sites. The demand follows Poisson distribution, which depends on the sale price of each product. Returned products arrive according to a Poisson process. Each returned product can be remanufactured, refurbished, or disposed. The time to manufacturing, refurbishing, and remanufacturing a product also follows an exponential distribution. By modeling the system as a Markov chain, the long-run expected profit function is obtained in terms of the dispose-down-to level of returned products and the order-up-to level and the sale price of serviceable products. A three-dimensional state space of the Markov Chain dependent to the sale price is developed considering pricing and inventory control decisions simultaneously with remanufacturing and refurbishing returned products. Since the model is a mixed integer nonlinear programming and known as complex models, the Artificial Bee Colony (ABC) algorithm, simulation and complete search method are used to solve the problem. The results show that by increasing the purchase price of the returned products, the amount of returned products will increase. If the refurbishing cost of the returned products is high or the disposal cost is low, less inventory should be kept in the system with a high price of serviceable products. If the lost sale cost is high, the more inventory should be maintained. Moreover, by decreasing the price elasticity of demand, the customer’s demand increases, and then more inventory should be maintained in the system.
Keywords: Hybrid production system, pricing, ABC algorithm, base stock
@article{RO_2021__55_5_2685_0,
author = {Naseri, Foruzan and Esmaeili, Maryam and Seifbarghy, Mehdi and Heydari, Tahereh},
title = {Pricing and inventory control decisions in the stochastic hybrid production systems with multiple recovery options},
journal = {RAIRO. Operations Research},
pages = {2685--2709},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
number = {5},
doi = {10.1051/ro/2021115},
mrnumber = {4313823},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2021115/}
}
TY - JOUR AU - Naseri, Foruzan AU - Esmaeili, Maryam AU - Seifbarghy, Mehdi AU - Heydari, Tahereh TI - Pricing and inventory control decisions in the stochastic hybrid production systems with multiple recovery options JO - RAIRO. Operations Research PY - 2021 SP - 2685 EP - 2709 VL - 55 IS - 5 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2021115/ DO - 10.1051/ro/2021115 LA - en ID - RO_2021__55_5_2685_0 ER -
%0 Journal Article %A Naseri, Foruzan %A Esmaeili, Maryam %A Seifbarghy, Mehdi %A Heydari, Tahereh %T Pricing and inventory control decisions in the stochastic hybrid production systems with multiple recovery options %J RAIRO. Operations Research %D 2021 %P 2685-2709 %V 55 %N 5 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2021115/ %R 10.1051/ro/2021115 %G en %F RO_2021__55_5_2685_0
Naseri, Foruzan; Esmaeili, Maryam; Seifbarghy, Mehdi; Heydari, Tahereh. Pricing and inventory control decisions in the stochastic hybrid production systems with multiple recovery options. RAIRO. Operations Research, Tome 55 (2021) no. 5, pp. 2685-2709. doi: 10.1051/ro/2021115
[1] and , Inventory optimization in a one product recoverable manufacturing system. Int. J. Prod. Econ. 124 (2010) 11–19. | DOI
[2] and , Life cycle inventory policy characterizations for a single-product recoverable system. Int. J. Prod. Econ. 124 (2010) 51–61. | DOI
[3] and , A modified artificial bee colony algorithm for numerical function optimization. In: 2012 IEEE symposium on computers and communications (ISCC). IEEE (2012) 000245–000249. | DOI
[4] , and , Assessing the benefits of remanufacturing option under one-way substitution. J. Oper. Res. Soc. 56 (2005) 286–296. | Zbl | DOI
[5] , and , Nonlinear Programming: Theory and Algorithms. John Wiley & Sons (2013). | Zbl
[6] and , Optimal manufacturing policy in a reverse logistic system with dependent stochastic returns and limited capacities. Int. J. Prod. Res. 51 (2013) 189–201. | DOI
[7] and , Non-convex mixed-integer nonlinear programming: a survey. Surv. Oper. Res. Manage. Sci. 17 (2012) 97–106. | MR
[8] , Optimal policy for a multiechelon inventory system with remanufacturing. Oper. Res. 54 (2006) 532–543. | MR | Zbl | DOI
[9] , , and , Reverse Logistics: Quantitative Models for Closed-Loop Supply Chains. Springer Science & Business Media (2013).
[10] , and , On the optimal control of manufacturing and remanufacturing activities with a single shared server. Eur. J. Oper. Res. 234 (2014) 86–98. | MR | Zbl | DOI
[11] , , and , Dynamic pricing and production control of an inventory system with remanufacturing. Math. Prob. Eng. 2015 (2015). | MR
[12] , and , Optimal product quality and pricing strategy for a twoperiod closed-loop supply chain with retailer variable markup. RAIRO:OR 53 (2019) 609–626. | MR | DOI
[13] , Optimal disposal policies for a single-item inventory system with returns. Naval Res. Logistics Q. 24 (1977) 385–405. | MR | Zbl | DOI
[14] , Simple optimal replenishment and disposal policies for a product recovery system with leadtimes. Oper. Res. Spectr. 19 (1997) 111–122. | MR | Zbl | DOI
[15] , Optimal policies in hybrid manufacturing/remanufacturing systems with product substitution. Int. J. Prod. Econ. 90 (2004) 325–343. | DOI
[16] and , Leadtime effects and policy improvement for stochastic inventory control with remanufacturing. Int. J. Prod. Econ. 71 (2001) 381–390. | DOI
[17] , A new approach for controlling a hybrid stochastic manufacturing/remanufacturing system with inventories and different leadtimes. Eur. J. Oper. Res. 147 (2003) 62–71. | Zbl | DOI
[18] , and , Exploring a productioninventory model with optimal reliability of the production in a parallel-series system. J. Ind. Prod. Eng. 37 (2020) 71–86.
[19] and , An analysis of single item inventory systems with returns. Naval Res. Logistics Q. 28 (1981) 237–254. | Zbl | DOI
[20] , and , Considering chain-to-chain competition on environmental and social concerns in a supply chain network design problem. Int. J. Manage. Sci. Eng. Manage. 14 (2019) 33–46.
[21] , Optimum solution structure for a repairable inventory problem. Oper. Res. 26 (1978) 270–281. | MR | Zbl | DOI
[22] , Green supply-chain management: a state-of-the-art literature review. Int. J. Manage. Rev. 9 (2007) 53–80. | DOI
[23] , , and , An adaptive pull strategy for remanufacturing systems. J. Intell. Manuf. 25 (2014) 629–645. | DOI
[24] , , and , Strategic issues in product recovery management. California Manage. Rev. 37 (1995) 114–136. | DOI
[25] and , Production planning and inventory control with remanufacturing and disposal. Eur. J. Oper. Res. 102 (1997) 264–278. | Zbl | DOI
[26] , , and , An inventory model with remanufacturing and disposal. Int. J. Prod. Econ. 46 (1996) 339–350. | DOI
[27] , and , Product remanufacturing and disposal: a numerical comparison of alternative control strategies. Int. J. Prod. Econ. 45 (1996) 489–498. | DOI
[28] , and , An investigation of lead-time effects in manufacturing/remanufacturing systems under simple push and pull control strategies. Eur. J. Oper. Res. 115 (1999) 195–214. | Zbl | DOI
[29] and , The value of dynamic pricing for cores in remanufacturing with backorders. J. Oper. Res. Soc. 64 (2013) 1314–1326. | DOI
[30] , , , , and , Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality. Int. J. Prod. Econ. 147 (2014) 678–688. | DOI
[31] and , Robust optimal inventory and acquisition effort decisions in a hybrid manufacturing/remanufacturing system. J. Ind. Prod. Eng. 36 (2019) 335–350.
[32] , , and , A hybrid two-stock inventory control model for a reverse supply chain. Transp. Res. Part E: Logistics Transp. Rev. 67 (2014) 141–161. | DOI
Cité par Sources :
