Open Access
Issue
RAIRO-Oper. Res.
Volume 56, Number 1, January-February 2022
Page(s) 275 - 292
DOI https://doi.org/10.1051/ro/2022006
Published online 07 February 2022
  • A.Y. Adhami and F. Ahmad, Interactive pythagorean-hesitant fuzzy computational algorithm for multiobjective transportation problem under uncertainty. Int. J. Manage. Sci. Eng. Manage. 15 (2020) 288–297. [Google Scholar]
  • A.Y. Adhami, F. Ahmad and N. Wani, Overall shale gas water management a neutrosophic optimization approach. In: Optimal Decision Making in Operations Research and Statistics: Methodologies and Applications. CRC Press (2021) 321. [Google Scholar]
  • F. Ahmad, Interactive neutrosophic optimization technique for multiobjective programming problems: an application to pharmaceutical supply chain management. Annals of Operations Research (2021) 1–35. DOI: 10.1007/s10479-021-03997-2. [Google Scholar]
  • F. Ahmad, Robust neutrosophic programming approach for solving intuitionistic fuzzy multiobjective optimization problems. Complex Intell. Syst. 7 (2021) 1935–1954. [CrossRef] [Google Scholar]
  • F. Ahmad and A.Y. Adhami, Neutrosophic programming approach to multiobjective nonlinear transportation problem with fuzzy parameters. Int. J. Manage. Sci. Eng. Manage. 14 (2019) 218–229. [Google Scholar]
  • F. Ahmad and B. John, A fuzzy quantitative model for assessing the performance of pharmaceutical supply chain under uncertainty. Kybernetes (2021). DOI: 10.1108/K-8-2021-070. [Google Scholar]
  • F. Ahmad and F. Smarandache, Neutrosophic fuzzy goal programming algorithm for multi-level multiobjective linear programming problems. Neutrosophic Operational Research, Springer (2021) 593–61. [CrossRef] [Google Scholar]
  • F. Ahmad, A.Y. Adhami and F. Smarandache, Single valued neutrosophic hesitant fuzzy computational algorithm for multiobjective nonlinear optimization problem. Neutrosophic Sets Syst. 22 (2018) 76–86. [Google Scholar]
  • F. Ahmad, A.Y. Adhami and F. Smarandache, Neutrosophic optimization model and computational algorithm for optimal shale gas water management under uncertainty. Symmetry 11 (2019) 544. [CrossRef] [Google Scholar]
  • F. Ahmad, S. Ahmad, A.T. Soliman and M. Abdollahian, Solving multi-level multiobjective fractional programming problem with rough interval parameter in neutrosophic environment. RAIRO-Oper. Res. 55 (2021) 2567–2581. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • F. Ahmad, S. Ahmad and M. Zaindin, A sustainable production and waste management policies for covid-19 medical equipment under uncertainty: a case study analysis. Comput. Ind. Eng. 157 (2021) 107381. [CrossRef] [Google Scholar]
  • F. Ahmad, S. Ahmad, M. Zaindin and A.Y. Adhami, A robust neutrosophic modeling and optimization approach for integrated energy-food-water security nexus management under uncertainty. Water 13 (2021) 121. [CrossRef] [Google Scholar]
  • F. Ahmad, K.A. Alnowibet, A.F. Alrasheedi and A.Y. Adhami, A multi-objective model for optimizing the socio-economic performance of a pharmaceutical supply chain. Soc.-Econ. Planning Sci. 79 (2021) 101126. [Google Scholar]
  • S. Ahmad, F. Ahmad and M. Sharaf, Supplier selection problem with type-2 fuzzy parameters: a neutrosophic optimization approach. Int. J. Fuzzy Syst. 23 (2021) 755–775. [CrossRef] [Google Scholar]
  • A.A.H. Ahmadini and F. Ahmad, A novel intuitionistic fuzzy preference relations for multiobjective goal programming problems. J. Intell. Fuzzy Syst. 40 (2021) 4761–4777. [CrossRef] [Google Scholar]
  • A.A.H. Ahmadini and F. Ahmad, Solving intuitionistic fuzzy multiobjective linear programming problem under neutrosophic environment. AIMS Math. 6 (2021) 4556–4580. [CrossRef] [MathSciNet] [Google Scholar]
  • R.E. Bellman and L.A. Zadeh, Decision-making in a fuzzy environment. Manage. Sci. 17 (1970) B-141–B-164. [Google Scholar]
  • S.K. Bharati, Hesitant fuzzy computational algorithm for multiobjective optimization problems. Int. J. Dyn. Control 6 (2018) 1799–1806. [CrossRef] [MathSciNet] [Google Scholar]
  • A. Biswas and N. Modak, A multiobjective fuzzy chance constrained programming model for land allocation in agricultural sector: a case study. Int. J. Comput. Intell. Syst. 10 (2017) 196–211. [CrossRef] [Google Scholar]
  • H. Cheng, W. Huang, Q. Zhou and J. Cai, Solving fuzzy multi-objective linear programming problems using deviation degree measures and weighted max–min method. Appl. Math. Modell. 37 (2013) 6855–6869. [CrossRef] [Google Scholar]
  • E.D. Dolan, The neos server 4.0 administrative guide. Technical Memorandum ANL/MCS-TM-250, Mathematics and Computer Science Division, Argonne National Laboratory (2001). [CrossRef] [Google Scholar]
  • L. Li and K.K. Lai, A fuzzy approach to the multiobjective transportation problem. Comput. Oper. Res. 27 (2000) 43–57. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Liu, Z. Xu and J. Gao, A fuzzy compromise programming model based on the modified s-curve membership functions for supplier selection. Granular Comput. 3 (2018) 275–283. [CrossRef] [Google Scholar]
  • S.K. Singh and S.P. Yadav, Modeling and optimization of multi objective non-linear programming problem in intuitionistic fuzzy environment. Appl. Math. Model. 39 (2015) 4617–4629. [CrossRef] [MathSciNet] [Google Scholar]
  • V. Torra and Y. Narukawa, On hesitant fuzzy sets and decision. In: 2009 IEEE International Conference on Fuzzy Systems . IEEE (2009) 1378–1382. [CrossRef] [Google Scholar]
  • S.-P. Wan, Y.-L. Qin and J.-Y. Dong, A hesitant fuzzy mathematical programming method for hybrid multi-criteria group decision making with hesitant fuzzy truth degrees. Knowl.-Based Syst. 138 (2017) 232–248. [CrossRef] [Google Scholar]
  • S.-P. Wan, Z. Jin and J.-Y. Dong, Pythagorean fuzzy mathematical programming method for multi-attribute group decision making with pythagorean fuzzy truth degrees. Knowl. Inf. Syst. 55 (2018) 437–466. [CrossRef] [Google Scholar]
  • S.-P. Wan, W.-C. Zou, L.-G. Zhong and J.-Y. Dong, Some new information measures for hesitant fuzzy promethee method and application to green supplier selection. Soft Comput. 24 (2020) 9179–9203. [CrossRef] [Google Scholar]
  • M. Xia and Z. Xu, Hesitant fuzzy information aggregation in decision making. Int. J. Approximate Reasoning 52 (2011) 395–407. [CrossRef] [Google Scholar]
  • M. Xia, Z. Xu and N. Chen, Some hesitant fuzzy aggregation operators with their application in group decision making. Group Decis. Negotiation 22 (2013) 259–279. [CrossRef] [Google Scholar]
  • G.-L. Xu, S.-P. Wan and J.-Y. Dong, A hesitant fuzzy programming method for hybrid madm with incomplete attribute weight information. Informatica 27 (2016) 863–892. [CrossRef] [Google Scholar]
  • J. Ye, Multiple-attribute decision-making method under a single-valued neutrosophic hesitant fuzzy environment. J. Intell. Syst. 24 (2015) 23–36. [CrossRef] [MathSciNet] [Google Scholar]
  • M. Zangiabadi and H.R. Maleki, Fuzzy goal programming technique to solve multiobjective transportation problems with some non-linear membership functions. Iran. J. Fuzzy Syst. 10 (2013) 61–74. [MathSciNet] [Google Scholar]
  • S. Zhang, C. Ka, M. Lee, K. Wu and K. Lun, Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels. Expert Syst. Appl. 65 (2016) 87–99. [CrossRef] [Google Scholar]
  • X. Zhang, Z. Xu and X. Xing, Hesitant fuzzy programming technique for multidimensional analysis of hesitant fuzzy preferences. OR Spectr. 38 (2016) 789–817. [CrossRef] [Google Scholar]
  • H.J. Zimmermann, Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst. 1 (1978) 45–55. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.