A comprehensive study of a backlogging EOQ model with nonlinear heptagonal dense fuzzy environment
RAIRO - Operations Research - Recherche Opérationnelle, Tome 54 (2020) no. 1, pp. 267-286.

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This paper deals with an adaptation of an application of nonlinear heptagonal dense fuzzy number. The concept of linear and as well as non-linear for both symmetric and asymmetric heptagonal dense fuzzy number is introduced here. We develop a new ranking method for non-linear heptagonal dense fuzzy number also. Considering a backorder inventory model with non-linear heptagonal dense fuzzy demand rate we have utilized a modified centroid method for defuzzification. For decision maker’s aspects, numerical examples, comparative study with other dense fuzzy numbers and a sensitivity analysis show the superiority of the nonlinear heptagonal dense fuzzy number. Finally, graphical illustrations are made to justify the model followed by a conclusion.

DOI : 10.1051/ro/2018114
Classification : 03E72, 90B50
Keywords: Heptagonal dense fuzzy number, centroid method, inventory problem, optimization
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     title = {A comprehensive study of a backlogging {EOQ} model with nonlinear heptagonal dense fuzzy environment},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
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Maity, Suman; Chakraborty, Avishek; De, Sujit Kumar; Mondal, Sankar Prasad; Alam, Shariful. A comprehensive study of a backlogging EOQ model with nonlinear heptagonal dense fuzzy environment. RAIRO - Operations Research - Recherche Opérationnelle, Tome 54 (2020) no. 1, pp. 267-286. doi : 10.1051/ro/2018114. http://geodesic.mathdoc.fr/articles/10.1051/ro/2018114/

[1] A. Felix and A.V. Devadoss, A new decagonal fuzzy number under uncertain linguistic environment. Int. J. Math. App. 3 (2015) 9–97.

[2] A.S. Sudha and S. Karunambigai, Solving a transportation problem using a Heptagonal fuzzy number. Int. J. Adv. Res. Sci. Eng. Technol. 4 (2017) 3118–3115.

[3] B. Asady, The revised method of ranking LR fuzzy number based on deviation Degree. Expert Syst. App. 37 (2010) 5056–5060. | DOI

[4] C.H. Cheng, A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst. 95 (1998) 307–317. | MR | Zbl | DOI

[5] D.P. Filev and R.R. Yager, A generalized defuzzification method via BADD Distributions. Int. J. Intell. Syst. 6 (1991) 687–697. | Zbl | DOI

[6] E. Shekarian, E.U. Olugu, S.H. Abdul-Rashid and E. Bottani, A fuzzy reverse logistics inventory system integrating economic order/production quantity models. Int. J. Fuzzy Syst. 18 (2016) 1141–1161. | MR | DOI

[7] E. Shekarian, E.U. Olugu, S.H. Abdul-Rashid and N. Kazemi, Analyzing optimization techniques in inventory models: the case of fuzzy economic order quantity problems. In: Int. Conference on Industrial Engineering and Operations Management. Kuala Lumpur, Malaysia, March 8-10 (2016) 1229–1240.

[8] E. Shekarian, E.U. Olugu, S.H. Abdul-Rashid and N. Kazemi, An economic order quantity model considering different holding costs for imperfect quality items subject to fuzziness and learning. J. Intell. Fuzzy Syst. 30 (2016) 2985–2997. | Zbl | DOI

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

[10] K. Rathi and S. Balamohan, A mathematical model for subjective evaluation of alternatives in Fuzzy multi-criteria group decision making using COPRAS method. Int. J. Fuzzy Syst. 19 (2017) 1290–1299. | DOI

[11] K. Rathi and S. Balamohan, Comparative study of arithmetic nature of Heptagonal fuzzy numbers. Appl. Math. Sci. 8 (2016) 4309–4321.

[12] K. Rathi, S. Balamohan, M. Revathi and B. Ananthi, A fuzzy approach for unequal workers-task assignment with heptagonal fuzzy numbers. Int. J. Recent Innov. Trends Comput. Commun. 4 (2016) 564–569.

[13] L.A. Zadeh, Fuzzy sets. Inf. Control 8 (1965) 338–353. | MR | Zbl | DOI

[14] L.H. Chen and H.W. Lu, An approximate approach for ranking fuzzy numbers based on left and right dominance. Comput. Math. Appl. 41 (2001) 1589–1602. | MR | Zbl | DOI

[15] L.H. Chen and H.W. Lu, The preference order of fuzzy numbers. Comput. Math. Appl. 44 (2002) 1455–1465. | MR | Zbl | DOI

[16] N.I. Namarta, N. Thakur and U.C. Gupta, Ranking of heptagonal fuzzy numbers using incentre of centroids. Int. J. Adv. Technol. Eng. Sci. 5 (2017) 248–255.

[17] N. Kazemi, E. Shekarian, L.E. Cárdenas-Barrón and E.U. Olugu, Incorporating human learning into a fuzzy EOQ inventory model with backorders. Comput. Ind. Eng. 87 (2015) 540–542. | DOI

[18] N. Kazemi, E.U. Olugu, A.-R. Salwa Hanim and R.A.B.R Ghazilla, A fuzzy EOQ model with backorders and forgetting effect on fuzzy parameters: an emperical study. Comput. Ind. Eng. 96 (2016) 140–148. | DOI

[19] N. Kazemi, E.U. Olugu, A.-R. Salwa Hanim and R.A.B.R Ghazilla, Development of a fuzzy economic order quantity model for imperfect quality items using the learning effect on fuzzy parameters. J. Intell. Fuzzy Syst. 28 (2015) 2377–2389. | MR | DOI

[20] P. Das, S.K. De and S.S. Sana, An EOQ model for time dependent backlogging over idle time: a step order fuzzy approach. Int. J. Appl. Comput. Math. 1 (2014) 1–17. | MR | Zbl

[21] Q. Song and R.P. Leland, Adaptive learning defuzzification techniques and applications. Comput. Math. Appl. 81 (1996) 321–329.

[22] R. Patro, M. Acharya, M.M. Nayak and S. Patnaik, A fuzzy EOQ model for deteriorating items with imperfect quality using proportionate discount under learning effects. Int. J. Manage. Decis. Making 17 (2018) | DOI

[23] R.R. Yager, Knowledge-based defuzzification. Fuzzy Sets Syst. 80 (1996) 177–185. | MR | DOI

[24] S. Abbasbandy and B. Asady, Ranking of fuzzy numbers by sign distance. Inf. Sci. 176 (2006) 2405–2416. | MR | Zbl | DOI

[25] S. Abbasbandy and T. Hajjari, A new approach for ranking of trapezoidal fuzzy Numbers. Comput. Math. Appl. 57 (2009) 413–419. | MR | Zbl | DOI

[26] S. Abbasbandy and T. Hajjari, An improvement on centroid point method for ranking of fuzzy numbers. J. Sci. I.A.U. 78 (2011) 109–119.

[27] S. Halgamuge, T. Runkler and M. Glesner, On the neural defuzzification Methods. In: Proceeding of the 5th IEEE International Conference on Fuzzy Systems (1996) 463–469.

[28] S.J. Chen and S.M. Chen, A new method for handling multicriteria fuzzy decision making problems using FN-IOWA operators. Cybern. Systems. 34 (2003) 109–137. | Zbl | DOI

[29] S.J. Chen and S.M. Chen, Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. Appl. Intell. 26 (2007) 1–11. | DOI

[30] S. Karmakar, S.K. De and A. Goswami, A pollution sensitive dense fuzzy economic production quantity model with cycle time dependent production rate. J. Cleaner Prod. 154 (2017) 139–150. | DOI

[31] S. Karmakar, S.K. De and A. Goswami, A pollution sensitive remanufacturing model with waste items: triangular dense fuzzy lock set approach. J. Cleaner Prod. 187 (2018) 789–803. | DOI

[32] S.K. De, A. Goswami and S.S. Sana, An interpolating by pass to Pareto optimality in intuitionistic fuzzy technique for a EOQ model with time sensitive backlogging. App. Math. Comput. 230 (2014) 664–674. | MR | Zbl | DOI

[33] S.K. De and G.C. Mahata, Decision of a fuzzy inventory with fuzzy backorder model under cloudy fuzzy demand rate. Int. J. Appl. Comput. Math. 3 (2017) 2593–2609. | MR | Zbl | DOI

[34] S.K. De and I. Beg, Triangular dense fuzzy Neutrosophic sets. Neutrosophic Sets Syst. 13 (2016) 1–12.

[35] S.K. De and I. Beg, Triangular dense fuzzy sets and new defuzzication methods. J. Intell. Fuzzy Syst. 31 (2016) 467–479. | Zbl

[36] S.K. De and S.S. Sana, An EOQ model with backlogging. Int. J. Manage. Sci. Eng. Manage. 11 (2016) 143–154.

[37] S.K. De and S.S. Sana, An alternative fuzzy EOQ model with backlogging for selling price and promotional effort sensitive demand. Int. J. Appl. Comput. Math. 1 (2015) 69–86. | MR | Zbl | DOI

[38] S.K. De and S.S. Sana, Backlogging EOQ model for promotional effort and selling price sensitive demand-an intuitionistic fuzzy approach. Ann. Oper. Res. 233 (2013) 57–76. | MR | Zbl

[39] S.K. De and S.S. Sana, Fuzzy order quantity inventory model with fuzzy shortage quantity and fuzzy promotional index. Econ. Model. 31 (2013) 351–358. | DOI

[40] S.K. De and S.S. Sana, The (p,q,r,l) model for stochastic demand under intuitionistic fuzzy aggregation with bonferroni mean. J. Intell. Manuf. 29 (2018) 1753–1771. | DOI

[41] S.K. De, EOQ model with natural idle time and wrongly measured demand rate. Int. J. Inventory Control Manage. 3 (2013) 329–354. | DOI

[42] S.K. De, Triangular dense fuzzy lock set. Soft Comput. 22 (2018) 7243–7254. | Zbl | DOI

[43] S.K. Sharma and S.M. Govindaluri, An analytical approach for EOQ determination using trapezoidal fuzzy function. Int. J. Procurement Manage. 11 (2018) 356–369. | DOI

[44] S. Maity, S.K. De and M. Pal, Two decision makers’ single decision over a back order EOQ model with dense fuzzy demand rate. Finance Market 3 (2018) 1–11. | DOI

[45] S.M. Chen and J.H. Chen, Fuzzy risk analysis based on the ranking of generalized fuzzy numbers with different heights and different spreads. Expert Syst. App. 36 (2009) 6833–6842. | DOI

[46] S. Selvakumari and S. Lavanya, Fuzzy game problem with payoffs as linguistic variables. Int. J. Eng. Sci. Manage. Res. 3 (2016) 18–24.

[47] S.S.L. Chang and L.A. Zadeh, On fuzzy mappings and control. IEEE Trans. Syst. Man Cybern. 2 (1972) 30–34. | MR | Zbl | DOI

[48] T. Chu and C. Tsao, Ranking fuzzy numbers with an area between the centroid point and original point. Comput. Math. Appl. 43 (2002) 111–117. | MR | Zbl | DOI

[49] T. Jiang and Y. Li, Generalized defuzzification strategies and their parameter learning procedure. IEEE Trans. Fuzzy Syst. 4 (1996) 64–71. | DOI

[50] T. Hajjari, On deviation degree methods for ranking fuzzy numbers. Aust. J. Basic App. Sci. 5 (2011) 750–758.

[51] T. Hajjari, Ranking of fuzzy numbers based on ambiguity degree. Aust. J. Basic App. Sci. 5 (2011) 62–69.

[52] U. Chanda and A. Kumar, Optimisation of fuzzy EOQ model for advertising and price sensitive demand model under dynamic ceiling on potential adoption. Int. J. Syst. Sci.: Oper. Logist. 4 (2017) 145–165.

[53] X.W. Liu and S.L. Han, Ranking fuzzy numbers with preference weighting function expectation. Comput. Math. Appl. 49 (2005) 1455–1465. | MR | Zbl

[54] Y. Deng and Q. Liu, A TOPSIS-based centroid index ranking method of fuzzy numbers and its application in decision-making. Cybern. Syst. 36 (2005) 581–595. | Zbl | DOI

[55] Y. Deng, Z.F. Zhu and Q. Liu, Ranking fuzzy numbers with an area method using of gyration. Comput. Math. Appl. 51 (2006) 1127–1136. | MR | Zbl | DOI

[56] Y.J. Wang and H.S. Lee, The revised method of ranking fuzzy numbers with an area between the centroid and original points. Comput. Math. Appl. 55 (2008) 2033–2042. | MR | Zbl | DOI

[57] Z.X. Wang, Y.J. Liu, Z.P. Fan and B. Feng, Ranking L-R fuzzy numbers based on deviation degree. Inf. Sci. 176 (2009) 2070–2077. | MR | Zbl | DOI

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