A Novel Algorithm to Find the Best Solution for Pentagonal Fuzzy Numbers with Linear Programming Problems
Main Article Content
Abstract
Fuzzy numbers are used in various fields such as fuzzy process methods, decision control theory, problems involving decision making, and systematic reasoning. Fuzzy systems, including fuzzy set theory. In this paper, pentagonal fuzzy variables (PFV) are used to formulate linear programming problems (LPP). Here, we will concentrate on an approach to addressing these issues that uses the simplex technique (SM). Linear programming problems (LPP) and linear programming problems (LPP) with pentagonal fuzzy numbers (PFN) are the two basic categories into which we divide these issues. The focus of this paper is to find the optimal solution (OS) for LPP with PFN on the objective function (OF) and right-hand side. New ranking function (RF) approaches for solving fuzzy linear programming problems (FLPP) with a pentagonal fuzzy number (PFN) have been proposed, based on new ranking functions (N RF). The simplex method (SM) is very easy to understand. Finally, numerical examples (NE) are used to demonstrate the suggested approach's computing process.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
licenseTermsHow to Cite
Publication Dates
References
Zaidan, A. A.; Atiya, B.; Abu Bakar, M. R.; Zaidan, B. B A new hybrid algorithm of simulated
annealing and simplex downhill for solving multiple-objective aggregate production planning on
fuzzy environment. Neural Computing and Applications, 2017, 31(6), 1823-1834.
Tanaka, H.; Okuda .T.; Asai. K. On fuzzy mathematical programming, The Journal of
Cybernetics,1974, 3, 37-46.
Mitlif, R. J. Development Lagrange Method for Solving Linear Fractional Programming
Problems with Intervals Coefficients in the Objective Function, Al-Mustansiriyah Journal of
Science, , 2016 , 27(1) , 88-90 .
Slevakumari , K.; Tamilarasi, R . Ranking of octagonal fuzzy numbers for solving fuzzy linear
Programming problems, International Journal of Engineering Research and Application,
Baghdad Science Journal , 2017, 7, 62-65,.
Onasanya , B.O.; Feng ,Y.; Wang , Z.; Samakin , O.V; Wu ,S. , Liu ,X. Optimizing Production
Mix Involving Linear Programming with Fuzzy Resources and Fuzzy Constraints, International
Journal of Computational Intelligence Systems, 2020 , 13(1), 727–733.
Ghadle, K. P.; Deshmukh, M. C.; Jadhav. O. S. A Novel Methodology for Decipher Mixed
Constraint Fuzzy Linear Programming Problem, Turkish Journal of Computer and Mathematics
Education, 2021, 12(14) , 606-612 .
Stephen, D. ; Kamalanathan, S. Solving Fuzzy Linear Programming Problem Using New
Ranking Procedures of Fuzzy Numbers , International Journal of Applications of Fuzzy Sets and
Artificial Intelligence , 2017 ,7 , 281-292.
Kalaf, B. A.; Bakar, R. A.; Soon, L. L.; Monsi, M. B.; Bakheet, A. J. K.; Abbas, I. T. A modified
fuzzy multi-objective linear programming to solve aggregate production planning. International
Journal of Pure and Applied Mathematics, 2015, 104(3), 339-352.
Nasseri,S. H. and Ardil , E. , Yazdani , A. and Zaefarian, R ., Simplex Method for Solving
Linear Programming Problems with Fuzzy Numbers, World Academy of Science, Engineering and
Technology , 2007, 10 , 877-881 .
Das, S. K. ; Chakraborty , A. A new approach to evaluate linear programming problem in
pentagonal neutrosophic environment , Complex & Intelligent Systems, 2020, 7(1) , 101–110 .
Dinagar , D. S. ; Jeyavuthin , M. M. Distinct Methods for Solving Fully Fuzzy Linear
Programming Problems with Pentagonal Fuzzy Numbers , Journal of Computer and Mathematical
Sciences, 2019 ,10 (6), 1253-1260.
Pathinathan . T.; Ponnivalavan .K. Pentagonal Fuzzy Number, International Journal of
Computing Algorithm Integrated Intelligent Research (IIR) , 2014 , 03, 1003-1005.