In this study, a novel algorithm is developed to solve the multi-level multiobjective fractional programming problems, using the idea of a neutrosophic fuzzy set. The co-efficients in each objective functions is assumed to be rough intervals. Furthermore, the objective functions are transformed into two sub-problems based on lower and upper approximation intervals. The marginal evaluation of pre-determined neutrosophic fuzzy goals for all objective functions at each level is achieved by different membership functions, such as truth, indeterminacy/neutral, and falsity degrees in neutrosophic uncertainty. In addition, the neutrosophic fuzzy goal programming algorithm is proposed to attain the highest degrees of each marginal evaluation goals by reducing their deviational variables and consequently obtain the optimal solution for all the decision-makers at all levels. To verify and validate the proposed neutrosophic fuzzy goal programming techniques, a numerical example is adressed in a hierarchical decision-making environment along with the conclusions.
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DOI : 10.1051/ro/2021108
Keywords: Rough intervals, Indeterminacy membership function, Neutrosophic goal programming algorithm, Hierarchical decision-making problems
@article{RO_2021__55_4_2567_0,
author = {Ahmad, Firoz and Ahmad, Shafiq and Soliman, Ahmed T. and Abdollahian, Mali},
title = {Solving multi-level multiobjective fractional programming problem with rough interval parameter in neutrosophic environment},
journal = {RAIRO. Operations Research},
pages = {2567--2581},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
number = {4},
doi = {10.1051/ro/2021108},
mrnumber = {4305770},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2021108/}
}
TY - JOUR AU - Ahmad, Firoz AU - Ahmad, Shafiq AU - Soliman, Ahmed T. AU - Abdollahian, Mali TI - Solving multi-level multiobjective fractional programming problem with rough interval parameter in neutrosophic environment JO - RAIRO. Operations Research PY - 2021 SP - 2567 EP - 2581 VL - 55 IS - 4 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2021108/ DO - 10.1051/ro/2021108 LA - en ID - RO_2021__55_4_2567_0 ER -
%0 Journal Article %A Ahmad, Firoz %A Ahmad, Shafiq %A Soliman, Ahmed T. %A Abdollahian, Mali %T Solving multi-level multiobjective fractional programming problem with rough interval parameter in neutrosophic environment %J RAIRO. Operations Research %D 2021 %P 2567-2581 %V 55 %N 4 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2021108/ %R 10.1051/ro/2021108 %G en %F RO_2021__55_4_2567_0
Ahmad, Firoz; Ahmad, Shafiq; Soliman, Ahmed T.; Abdollahian, Mali. Solving multi-level multiobjective fractional programming problem with rough interval parameter in neutrosophic environment. RAIRO. Operations Research, Tome 55 (2021) no. 4, pp. 2567-2581. doi: 10.1051/ro/2021108
[1] and , Fuzzy goal programming procedure to bilevel multiobjective linear fractional programming problems. Int. J. Math. Math. Sci. 2010 (2010). | MR | Zbl
[2] and , Interactive pythagorean-hesitant fuzzy computational algorithm for multiobjective transportation problem under uncertainty. Int. J. Manag. Sci. Eng. Manag. 15 (2020) 1–10.
[3] , Interactive neutrosophic optimization technique for multiobjective programming problems: an application to pharmaceutical supply chain management. Ann. Oper. Res. (2021a) 1–35. | MR
[4] , Robust neutrosophic programming approach for solving intuitionistic fuzzy multiobjective optimization problems. Complex Intell. Syst. (2021b) 1–20.
[5] and , Neutrosophic programming approach to multiobjective nonlinear transportation problem with fuzzy parameters. Int. J. Manag. Sci. Eng. Manag. 14 (2019a) 218–229.
[6] and , Total cost measures with probabilistic cost function under varying supply and demand in transportation problem. Opsearch 56 (2019b) 583–602. | MR | Zbl | DOI
[7] , and , Single Valued Neutrosophic Hesitant Fuzzy Computational Algorithm for Multiobjective Nonlinear Optimization Problem. Neutrosophic Sets Syst. 22 (2018) 76–86.
[8] , and , Neutrosophic optimization model and computational algorithm for optimal shale gas water management under uncertainty. Symmetry 11 (2019). | DOI
[9] , and , Modified neutrosophic fuzzy optimization model for optimal closed-loop supply chain management under uncertainty. In Optimization theory based on neutrosophic and plithogenic sets, Elsevier (2020) 343–403.
[10] , and , A sustainable production and waste management policies for covid-19 medical equipment under uncertainty: A case study analysis. Comput. Ind. Eng. 157 (2021) 107381. | DOI
[11] , and , Supplier selection problem with type-2 fuzzy parameters: A neutrosophic optimization approach. Int. J. Fuzzy Syst. 23 (2021) 755–775. | DOI
[12] and , A novel intuitionistic fuzzy preference relations for multiobjective goal programming problems. Int. J. Fuzzy Syst. 40 (2021a) 4761–4777.
[13] and , Solving intuitionistic fuzzy multiobjective linear programming problem under neutrosophic environment. AIMS Math. 6 (2021b) 4556–4580. | MR | DOI
[14] , Application of rough set theory as a new approach to simplify dams location. Sci. Iran. 13 (2006).
[15] , The neos server 4.0 administrative guide. Tech. Technical report, Memorandum ANL/MCS-TM-250, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA (2001)
[16] , and , Linear programming with rough interval coefficients. J. Intell. Fuzzy Syst. 26 (2014) 1179–1189. | MR | Zbl | DOI
[17] , , , and , Simultaneous customers and supplier’s prioritization: An ahp-based fuzzy inference decision support system (ahp-fidss). Int. J. Fuzzy Syst. 22 (2020) 2625–2651. | DOI
[18] and , Mathematical solution of multilevel fractional programming problem with fuzzy goal programming approach. J. Ind. Eng. Int. 8 (2012) 16. | DOI
[19] , , , and , Development of a fuzzy economic order quantity model of deteriorating items with promotional effort and learning in fuzziness with a finite time horizon. Inventions 4 (2019) 36. | DOI
[20] and , Coordinating supply-chain management under stochastic fuzzy environment and lead-time reduction. Mathematics 7 (2019) 480. | DOI
[21] , Weighting method for bi-level linear fractional programming problems. Eur. J. Oper. Res. 183 (2007) 296–302. | Zbl | DOI
[22] and , On multi-level multi-objective linear fractional programming problem with interval parameters. RAIRO-Operations Research 53 (2019) 1601–1616. | MR | Zbl | Numdam | DOI
[23] , and , Solving multi-level multi-objective fractional programming problems with fuzzy demands via fgp approach. Int. J. Appl. Comput. Math. 4 (2018) 41. | MR | Zbl | DOI
[24] , , and , Solving multi-level multi-objective fractional programming problem with rough intervals in the objective functions. J. adv. math. Comput. Sci. (2017) 1–17.
[25] , Rough sets. Int. J. Comput. Inf. Syst. 11 (1982) 341–356. | MR | Zbl | DOI
[26] and , Rudiments of rough sets. Inf. Sci. 177 (2007) 3–27. | MR | Zbl | DOI
[27] and , Fuzzy goal programming approach to multilevel programming problems. Eur. J. Oper. Res. 176 (2007) 1151–1166. | Zbl | DOI
[28] , , , and , Novel concepts in intuitionistic fuzzy graphs with application. J. Intell. Fuzzy Syst. 37 (2019) 3743–3749. | DOI
[29] , and , A multi-objective transportation model under neutrosophic environment. Comput. Electr. Eng. 69 (2018) 705–719. | DOI
[30] , State-of-the-Art Solvers for Numerical Optimization (2016).
[31] , A unifying field in logics: Neutrosophic logic. In Philosophy, American Research Press (1999) 1–141. | Zbl
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