Designing a single-vendor and multiple-buyers’ integrated production inventory model for interval type-2 fuzzy demand and fuzzy rule based deterioration
RAIRO. Operations Research, Tome 55 (2021) no. 6, pp. 3715-3742

In this paper, a single-vendor and multiple-buyers’ integrated production inventory model is investigated where demand of the item at the buyers’ location is considered as interval type-2 fuzzy number (IT2FN). Deterioration rate of the item is assumed to change in accordance with the weather conditions of a particular region. It relies upon the values of certain attributes that have a direct influence on the extent of deterioration. These parameter values are easily forecasted and thereby can be utilized to determine the item depletion rate, which is executed here using Mamdani fuzzy inference scheme. Besides, a nearest interval approximation formula for the defuzzification of IT2FN is developed and applied in the proposed integrated production inventory model. The model optimizes the total number of shipments to be made to the buyers within a complete cycle so as to minimize the overall integrated cost incurred. A detailed illustration of the theoretical results is further demonstrated with the help of numerical example, followed by sensitivity analysis which provides insights into better decision making.

DOI : 10.1051/ro/2021174
Classification : 90B06
Keywords: Interval type-2 fuzzy number, nearest interval approximation, vendor–buyer coordination, production inventory, Fuzzy rule based deterioration
@article{RO_2021__55_6_3715_0,
     author = {Rout, Chayanika and Kumar, Ravi Shankar and Paul, Arjun and Chakraborty, Debjani and Goswami, Adrijit},
     title = {Designing a single-vendor and multiple-buyers{\textquoteright} integrated production inventory model for interval type-2 fuzzy demand and fuzzy rule based deterioration},
     journal = {RAIRO. Operations Research},
     pages = {3715--3742},
     year = {2021},
     publisher = {EDP-Sciences},
     volume = {55},
     number = {6},
     doi = {10.1051/ro/2021174},
     mrnumber = {4353560},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/ro/2021174/}
}
TY  - JOUR
AU  - Rout, Chayanika
AU  - Kumar, Ravi Shankar
AU  - Paul, Arjun
AU  - Chakraborty, Debjani
AU  - Goswami, Adrijit
TI  - Designing a single-vendor and multiple-buyers’ integrated production inventory model for interval type-2 fuzzy demand and fuzzy rule based deterioration
JO  - RAIRO. Operations Research
PY  - 2021
SP  - 3715
EP  - 3742
VL  - 55
IS  - 6
PB  - EDP-Sciences
UR  - https://www.numdam.org/articles/10.1051/ro/2021174/
DO  - 10.1051/ro/2021174
LA  - en
ID  - RO_2021__55_6_3715_0
ER  - 
%0 Journal Article
%A Rout, Chayanika
%A Kumar, Ravi Shankar
%A Paul, Arjun
%A Chakraborty, Debjani
%A Goswami, Adrijit
%T Designing a single-vendor and multiple-buyers’ integrated production inventory model for interval type-2 fuzzy demand and fuzzy rule based deterioration
%J RAIRO. Operations Research
%D 2021
%P 3715-3742
%V 55
%N 6
%I EDP-Sciences
%U https://www.numdam.org/articles/10.1051/ro/2021174/
%R 10.1051/ro/2021174
%G en
%F RO_2021__55_6_3715_0
Rout, Chayanika; Kumar, Ravi Shankar; Paul, Arjun; Chakraborty, Debjani; Goswami, Adrijit. Designing a single-vendor and multiple-buyers’ integrated production inventory model for interval type-2 fuzzy demand and fuzzy rule based deterioration. RAIRO. Operations Research, Tome 55 (2021) no. 6, pp. 3715-3742. doi: 10.1051/ro/2021174

[1] D. Chakraborty and S. K. Bhuiya, A continuous review inventory model with fuzzy service level constraint and fuzzy random variable parameters. Int. J. Appl. Comput. Math. 3 (2017) 3159–3174. | MR | DOI

[2] D. Chakraborty, D. Guha and B. Dutta, Multi-objective optimization problem under fuzzy rule constraints using particle swarm optimization. Soft Comput. 20 (2016) 2245–2259. | DOI

[3] C. K. Chan, W. H. Wong, A. Langevin and Y. Lee, An integrated production-inventory model for deteriorating items with consideration of optimal production rate and deterioration during delivery. Int. J. Prod. Econ. 189 (2017) 1–13. | DOI

[4] H.-C. Chang, J.-S. Yao and L.-Y. Ouyang, Fuzzy mixture inventory model involving fuzzy random variable lead time demand and fuzzy total demand. Eur. J. Oper. Res. 169 (2006) 65–80. | MR | Zbl | DOI

[5] Z. Chen, Optimization of production inventory with pricing and promotion effort for a single-vendor multi-buyer system of perishable products. Int. J. Prod. Econ. 203 (2018) 333–349. | DOI

[6] S.-M. Chen and L.-W. Lee, Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets. Expert Syst. App. 37 (2010) 824–833. | DOI

[7] T.-Y. Chen, C.-H. Chang and J.-F. R. Lu, The extended qualiflex method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making. Eur. J. Oper. Res. 226 (2013) 615–625. | MR | Zbl | DOI

[8] X. Chen, S. Benjaafar and A. Elomri, The carbon-constrained EOQ. Oper. Res. Lett. 41 (2013) 172–179. | MR | Zbl | DOI

[9] M. Cococcioni, P. Ducange, B. Lazzerini and F. Marcelloni, A pareto-based multi-objective evolutionary approach to the identification of mamdani fuzzy systems. Soft Comput. 11 (2007) 1013–1031. | DOI

[10] S. Coupland and R. John, A fast geometric method for defuzzification of type-2 fuzzy sets. IEEE Trans. Fuzzy Syst. 16 (2008) 929–941. | DOI

[11] S. K. De and A. Goswami, A replenishment policy for items with finite production rate and fuzzy deterioration rate. OPSEARCH 38 (2001) 419–430. | DOI

[12] S. K. De, P. K. Kundu and A. Goswami, An economic production quantity inventory model involving fuzzy demand rate and fuzzy deterioration rate. J. Appl. Math. Comput. 12 (2003) 251. | MR | Zbl | DOI

[13] O. Dey and D. Chakraborty, A fuzzy random continuous review inventory system. Int. J. Prod. Econ. 132 (2011) 101–106. | DOI

[14] O. Dey and D. Chakraborty, A fuzzy random periodic review system with variable lead-time and negative exponential crashing cost. Appl. Math. Model. 36 (2012) 6312–6322. | MR | DOI

[15] B. K. Dey, B. Sarkar, M. Sarkar and S. Pareek, An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment. RAIRO-Oper. Res. 53 (2019) 39–57. | MR | Numdam | DOI

[16] D. Dubois and H. Prade, Operations on fuzzy numbers. Int. J. Syst. Sci. 9 (1978) 613–626. | MR | Zbl | DOI

[17] P. Dutta, D. Chakraborty and A. R. Roy, A single-period inventory model with fuzzy random variable demand. Math. Comput. Model. 41 (2005) 915–922. | MR | Zbl | DOI

[18] P. Dutta, D. Chakraborty and A. Roy, Continuous review inventory model in mixed fuzzy and stochastic environment. Appl. Math. Comput. 188 (2007) 970–980. | MR | Zbl

[19] P. Ghare, A model for an exponentially decaying inventory. J. Ind. Eng. 14 (1963) 238–243.

[20] S. Greenfield and F. Chiclana, Type-reduced set structure and the truncated type-2 fuzzy set. Fuzzy Sets Syst. 352 (2018) 119–141. | MR | DOI

[21] S. Greenfield, F. Chiclana, S. Coupland and R. John, The collapsing method of defuzzification for discretised interval type-2 fuzzy sets. Information Sciences 179 (2009) 2055–2069. | MR | Zbl | DOI

[22] S. Greenfield, F. Chiclana, R. John and S. Coupland, The sampling method of defuzzification for type-2 fuzzy sets: experimental evaluation. Inf. Sci. 189 (2012) 77–92. | MR | DOI

[23] P. Grzegorzewski, Nearest interval approximation of a fuzzy number. Fuzzy Sets Syst. 130 (2002) 321–330. | MR | Zbl | DOI

[24] V. Hovelaque and L. Bironneau, The carbon-constrained EOQ model with carbon emission dependent demand. Int. J. Prod. Econ. 164 (2015) 285–291. | DOI

[25] T. Jia, Y. Liu, N. Wang and F. Lin, Optimal production-delivery policy for a vendor–buyers integrated system considering postponed simultaneous delivery. Comput. Ind. Eng. 99 (2016) 1–15. | DOI

[26] N. N. Karnik and J. M. Mendel, Centroid of a type-2 fuzzy set. Inf. Sci. 132 (2001) 195–220. | MR | Zbl | DOI

[27] A. Khanna, P. Gautam, B. Sarkar and C. K. Jaggi, Integrated vendor–buyer strategies for imperfect production systems with maintenance and warranty policy. RAIRO-Oper. Res. 54 (2020) 435–450. | MR | Numdam | DOI

[28] R. S. Kumar and A. Goswami, A continuous review production–inventory system in fuzzy random environment: minmax distribution free procedure. Comput. Ind. Eng. 79 (2015) 65–75. | DOI

[29] R. S. Kumar, M. Tiwari and A. Goswami, Two-echelon fuzzy stochastic supply chain for the manufacturer-buyer integrated production-inventory system. J. Intell. Manuf. 27 (2016) 875–888. | DOI

[30] Y.-P. Lee and C.-Y. Dye, An inventory model for deteriorating items under stock-dependent demand and controllable deterioration rate. Comput. Ind. Eng. 63 (2012) 474–482. | DOI

[31] J. Li, R. John, S. Coupland and G. Kendall, On Nie-Tan operator and type-reduction of interval type-2 fuzzy sets. IEEE Trans. Fuzzy Syst. 26 (2017) 1036–1039. | DOI

[32] G. Li, X. He, J. Zhou and H. Wu, Pricing, replenishment and preservation technology investment decisions for non-instantaneous deteriorating items. Omega 84 (2019) 114–126. | DOI

[33] Y. Liang and F. Zhou, A two-warehouse inventory model for deteriorating items under conditionally permissible delay in payment. Appl. Math. Model. 35 (2011) 2221–2231. | MR | Zbl | DOI

[34] S.-T. Lo, H.-M. Wee and W.-C. Huang, An integrated production-inventory model with imperfect production processes and weibull distribution deterioration under inflation. Int. J. Prod. Econ. 106 (2007) 248–260. | DOI

[35] X. Ma, P. Wu, L. Zhou, H. Chen, T. Zheng and J. Ge, Approaches based on interval type-2 fuzzy aggregation operators for multiple attribute group decision making. Int. J. Fuzzy Syst. 18 (2016) 697–715. | MR | DOI

[36] J. M. Mendel and X. Liu, New closed-form solutions for karnik-mendel algorithm+ defuzzification of an interval type-2 fuzzy set. In: 2012 IEEE International Conference on Fuzzy Systems. IEEE (2012) 1–8.

[37] D. J. Mohanty, R. S. Kumar and A. Goswami, A two-warehouse inventory model for non-instantaneous deteriorating items over stochastic planning horizon. J. Ind. Prod. Eng. 33 (2016) 516–532.

[38] D. J. Mohanty, R. S. Kumar and A. Goswami, Vendor-buyer integrated production-inventory system for imperfect quality item under trade credit finance and variable setup cost. RAIRO-Oper. Res. 52 (2018) 1277–1293. | MR | Zbl | Numdam | DOI

[39] J. E. Moreno, M. A. Sanchez, O. Mendoza, A. Rodríguez-Díaz, O. Castillo, P. Melin and J. R. Castro, Design of an interval type-2 fuzzy model with justifiable uncertainty. Inf. Sci. 513 (2020) 206–221. | DOI

[40] M. Nie and W. W. Tan, Towards an efficient type-reduction method for interval type-2 fuzzy logic systems. In: Fuzzy Systems, 2008. FUZZ-IEEE 2008 (IEEE World Congress on Computational Intelligence). IEEE International Conference on Fuzzy Systems. IEEE (2008) 1425–1432.

[41] L.-Y. Ouyang, K.-S. Wu and C.-T. Yang, A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments. Comput. Ind. Eng. 51 (2006) 637–651. | DOI

[42] B. Pal, A. Mandal and S. S. Sana, Two-phase deteriorated supply chain model with variable demand and imperfect production process under two-stage credit financing. RAIRO-Oper. Res. 55 (2021) 457–480. | MR | Numdam | DOI

[43] V. Pando, L. A. San-José, J. García-Laguna and J. Sicilia, Optimal lot-size policy for deteriorating items with stock-dependent demand considering profit maximization. Comput. Ind. Eng. 117 (2018) 81–93. | DOI

[44] H. Rau, M.-Y. Wu and H.-M. Wee, Integrated inventory model for deteriorating items under a multi-echelon supply chain environment. Int. J. Prod. Econ. 86 (2003) 155–168. | DOI

[45] C. Rout, R. S. Kumar, D. Chakraborty and A. Goswami, An EPQ model for deteriorating items with imperfect production, inspection errors, rework and shortages: a type-2 fuzzy approach. OPSEARCH 56 (2019) 657–688. | MR | DOI

[46] C. Rout, A. Paul, R. S. Kumar, D. Chakraborty and A. Goswami, Cooperative sustainable supply chain for deteriorating item and imperfect production under different carbon emission regulations. J. Cleaner Prod. 272 (2020) 122170. | DOI

[47] C. Rout, D. Chakraborty and A. Goswami, An EPQ model for deteriorating items with imperfect production, two types of inspection errors and rework under complete backordering. Int. Game Theory Rev. 22 (2020) 2040011. | MR | DOI

[48] C. Rout, D. Chakraborty and A. Goswami, A production inventory model for deteriorating items with backlog-dependent demand. RAIRO-Oper. Res. 55 (2021) S549–S570. | MR | DOI

[49] T. A. Runkler, C. Chen and R. John, Type reduction operators for interval type-2 defuzzification. Inf. Sci. 467 (2018) 464–476. | MR | DOI

[50] 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. | MR | Numdam | DOI

[51] S. Sarkar, B. C. Giri and A. K. Sarkar, A vendor–buyer inventory model with lot-size and production rate dependent lead time under time value of money. RAIRO-Oper. Res. 54 (2020) 961–979. | MR | Zbl | Numdam | DOI

[52] A. Sengupta and T. K. Pal, Fuzzy Preference Ordering of Interval Numbers in Decision Problems. Springer. Vol. 238 (2009). | MR | Zbl | DOI

[53] A. Sengupta, T. K. Pal and D. Chakraborty, Interpretation of inequality constraints involving interval coefficients and a solution to interval linear programming. Fuzzy Sets Syst. 119 (2001) 129–138. | MR | Zbl | DOI

[54] A. K. Sharma, S. Tiwari, V. Yadavalli and C. K. Jaggi, Optimal trade credit and replenishment policies for non-instantaneous deteriorating items. RAIRO-Oper. Res. 54 (2020) 1793–1826. | MR | Numdam | DOI

[55] E. Shekarian, N. Kazemi, S. H. Abdul-Rashid and E. U. Olugu, Fuzzy inventory models: a comprehensive review. Appl. Soft Comput. 55 (2017) 588–621. | DOI

[56] K. Skouri, I. Konstantaras, S. Papachristos and I. Ganas, Inventory models with ramp type demand rate, partial backlogging and weibull deterioration rate. Eur. J. Oper. Res. 192 (2009) 79–92. | MR | Zbl | DOI

[57] A. H. Tai, Y. Xie, W. He and W.-K. Ching, Joint inspection and inventory control for deteriorating items with random maximum lifetime. Int. J. Prod. Econ. 207 (2019) 144–162. | DOI

[58] A. A. Taleizadeh, S. T. Niaki and A. Makui, Multiproduct multiple-buyer single-vendor supply chain problem with stochastic demand, variable lead-time, and multi-chance constraint. Expert Syst. App. 39 (2012) 5338–5348. | DOI

[59] A. D. Torshizi and M. H. F. Zarandi, Hierarchical collapsing method for direct defuzzification of general type-2 fuzzy sets. Inf. Sci. 277 (2014) 842–861. | MR | Zbl | DOI

[60] A. D. Torshizi, M. H. F. Zarandi and H. Zakeri, On type-reduction of type-2 fuzzy sets: a review. Appl. Soft Comput. 27 (2015) 614–627. | DOI

[61] G. A. Widyadana and H. M. Wee, An economic production quantity model for deteriorating items with multiple production setups and rework. Int. J. Prod. Econ. 138 (2012) 62–67. | DOI

[62] G. A. Widyadana, L. E. Cárdenas-Barrón and H. M. Wee, Economic order quantity model for deteriorating items with planned backorder level. Math. Comput. Model. 54 (2011) 1569–1575. | MR | Zbl | DOI

[63] K.-S. Wu, L.-Y. Ouyang and C.-T. Yang, An optimal replenishment policy for non-instantaneous deteriorating items with stock-dependent demand and partial backlogging. Int. J. Prod. Econ. 101 (2006) 369–384. | DOI

[64] C. Yan, A. Banerjee and L. Yang, An integrated production–distribution model for a deteriorating inventory item. Int. J. Prod. Econ. 133 (2011) 228–232. | DOI

[65] P.-C. Yang and H.-M. Wee, A single-vendor and multiple-buyers production-inventory policy for a deteriorating item. Eur. J. Oper. Res. 143 (2002) 570–581. | MR | Zbl | DOI

[66] M.-J. Yao and C.-C. Chiou, On a replenishment coordination model in an integrated supply chain with one vendor and multiple buyers. Eur. J. Oper. Res. 159 (2004) 406–419. | MR | Zbl | DOI

[67] S. H. Yoo, D. Kim and M.-S. Park, Economic production quantity model with imperfect-quality items, two-way imperfect inspection and sales return. Int. J. Prod. Econ. 121 (2009) 255–265. | DOI

Cité par Sources :