Use of “e” and “g” operators to a fuzzy production inventory control model for substitute items
RAIRO - Operations Research - Recherche Opérationnelle, Tome 53 (2019) no. 2, pp. 473-486.

In this paper, a fuzzy optimal control model for substitute items with stock and selling price dependent demand has been developed. Here the state variables (stocks) are assumed to be fuzzy variables. So the proposed dynamic control system can be represented as a fuzzy differential system which optimize the profit of the production inventory control model through Pontryagin’s maximum principle. The proposed fuzzy control problem has been transformed into an equivalent crisp differential system using “e” and “g” operators. The deterministic system is then solved by using Newton’s forward-backward method through MATLAB. Finally some numerical results are presented both in tabular and graphical form.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2017047
Classification : 49J15, 90C70
Mots-clés : Fuzzy dynamical system, “e” and “g” operators, Production-inventory control, Substitute items, Stock and selling price dependent demand
Khatua, Debnarayan 1 ; De, Anupam 1 ; Maity, Kalipada 1 ; Kar, Samarjit 1

1
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     title = {Use of {\textquotedblleft}e{\textquotedblright} and {\textquotedblleft}g{\textquotedblright} operators to a fuzzy production inventory control model for substitute items},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {473--486},
     publisher = {EDP-Sciences},
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Khatua, Debnarayan; De, Anupam; Maity, Kalipada; Kar, Samarjit. Use of “e” and “g” operators to a fuzzy production inventory control model for substitute items. RAIRO - Operations Research - Recherche Opérationnelle, Tome 53 (2019) no. 2, pp. 473-486. doi : 10.1051/ro/2017047. http://archive.numdam.org/articles/10.1051/ro/2017047/

[1] M.Z. Ahmad, M.K. Hasan and B. De Baets, Analytical and numerical solutions of fuzzy differential equations. Inf. Sci. 236 (2013) 156–167. | Zbl

[2] A. Bartoszewicz and P. Lesniewski, Reaching Law Approach to the Sliding Mode Control of Periodic Review Inventory Systems. IEEE Trans. Automation Sci. Eng. 11 (2014) 810–817.

[3] L. Chen, Y. Chen and Z. Pang, Dynamic Pricing and Inventory Control in a Make-to-Stock Queue With Information on the Production Status. IEEE Trans. Automation Sci. Eng. 8 (2011) 361–373.

[4] A. Chernev, Product Assortment and Consumer Choice: An Interdisciplinary Review, In Vol. 6 (2011) 1–61.

[5] M.S. El Naschie, From experimental quantum optics to quantum gravity via a fuzzy kahler manifold. Chaos Solitons Fract 25 (2005) 969–977. | Zbl

[6] A.F. Jameel, A.I.M. Ismail and F. Mabood, Optimal homotopy asymptotic method for solving nth order linear fuzzy initial value problems. J. Assoc. Arab Univers. Basic and Appl. Sci. 21 (2016) 77–85.

[7] X.-C. Jia, X.-B. Chi, Q.-L. Han and N.-N. Zheng, Event-triggered fuzzy H control for a class of nonlinear networked control systems using the deviation bounds of a synchronous normalized membership functions. Inf. Sci. 259 (2014) 100–117. | Zbl

[8] S. Hazari, K. Maity, J.K. Dey and S. Kar, Optimal dynamic production and pricing for reliability depended imperfect production with inventory-level-dependent demand in uncertain environment. J. Uncertainty Anal. Appl. 2 (2015) 1–17.

[9] A. Katsifou, R.W. Seifert and J. Tancrez, Joint productassortment, inventory and price optimization to attract loyal and non-loyal customers. Omega 46 (2014) 36–50.

[10] M. Khan and M.Y. Jaber, Optimal inventory cycle in a two-stage supply chain incorporating imperfect items from suppliers. Inter. J. Operat. Res. 10 (2011) 442–457. | Zbl

[11] A. De, K. Maity and M. Maiti, Stability analysis of a combined project of fish, broiler and ducks: Dynamical system in imprecise envioronment. Inter. J. Biomath. 8 (2015) 1550067. | Zbl

[12] C. Krishnamoorthi and S. Panayappan, An EPQ model for an imperfect production system with rework and shortages. Int. J. Operat. Res. 17 (2013) 104–124. | Zbl

[13] K. Maity and M. Maiti, Optimal inventory policies for deteriorating complementary and substitute items. Inter. J. Syst. Sci. 40 (2009) 267–276. | Zbl

[14] K. Maity and M. Maiti, Inventory of deteriorating complementary and substitute items with stock dependent demand. Amer. J. Math. Manag. Sci. 25 (2005) 83–96. | Zbl

[15] M. Mazandarani and M. Najariyan, A note on “A class of linear differential dynamical systems with fuzzy initial condition”. Fuzzy Sets Syst. 265 (2015) 121–126. | Zbl

[16] M. Najariyan and M.H. Farahi, Optimal control of fuzzy linear controlled system with fuzzy initial conditions. Iranian J. Fuzzy Syst. 10 (2013) 21–35. | Zbl

[17] A. Omer and O. Omer, A pray and predator model with fuzzy initial values. J. Math. Stat. 41 (2013) 387–395. | Zbl

[18] E.L. Porteus, Optimal lot sizing, process quality improvement and setup cost reduction. Operat. Res. 34 (1986) 137–144. | Zbl

[19] L.S. Pontryagin and V.G. Boltyanski, The Mathematical Theory Optimal Process. Inter. Sci., New York (1962).

[20] D. Panda, S. Kar, K. Maity and M. Maity, A single period inventory model with imperfect production and stochastic demand under chance and imprecise constraints. Eur. J. Operat. Res. 188 (2008) 121–139. | Zbl

[21] S. Ramezanzadeh and A. Heydari, Optimal control with fuzzy chance constraint. Iranian J. fuzzy Syst. 8 (2011) 35–43. | Zbl

[22] C.K. Sivashankari and S. Panayappan, Production inventory model with reworking of imperfect production. Inter. J. Manag. Sci. Eng. Manag. 9 (2014) 9–20.

[23] D. Filev and P. Angelove, Fuzzy optimal control. Fuzzy Sets and Syst. 47 (1992) 151–56. | Zbl

[24] D. Yadav, S.R. Singh and R. Kumari, Three-stage supply chain coordination under fuzzy random demand and production rate with imperfect production process. Int. J. Operat. Res. 16 (2013) 421–447. | Zbl

[25] P.K. Sahu and S. Ray, Two-dimensional Legendre wavelet method for the numerical solutions of fuzzy integro-differential equations. J. Intell. Fuzzy Syst. 28 (2015) 1271–1279. | Zbl

[26] S.S. Sana, A production-inventory model of imperfect quality products in a three-layer supply chain. Decision Support System 50 (2011) 539–547.

[27] Z.-P. Wang and H.-N. Wu, Finite dimensional guaranteed cost sampled data fuzzy control for a class of nonlinear distributed parameter systems and Information Sci. 327 (2016) 21–39. | Zbl

[28] Y. Zhu, A fuzzy optimal control model. J. Uncertain Syst. 3 (2009) 270–279.

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