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Abstract

In this paper, we have proposed a new technique to find an efficient solution to fractional programming problems (FPP). The multi-objective fractional programming problem (MOFPP) is converted into multi-objective linear programming (MOLPP) utilizing the point-slopes formula for a plane, which has equivalent weights to the MOFPP. The MOLPP is diminished to a single objective linear programming problem (SOLPP) through using two new techniques for the values of the objective function and suggesting an algorithm for its solution. Finally, we obtained the optimal solution for MOFPP by solving the consequent linear programming problem (LPP). The proposed practicability is confirmed with the existing approaches, with some numerical examples and we indicated comparison with other techniques. 

Keywords

Multi-Objective Linear Fractional Programming Problem Multi-Objective Quadratic Fractional Programming Problem Point-Slopes Formula Mean Deviation

Article Details

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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CC BY: This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

 

Author Biography

Rebaz Mustafa, Department of Management Information System, Erbil Technical Administrative Institute, Erbil Polytechnic University, Erbil, Iraq

Department of Mathematics, College of Education, Salahaddin University, Erbil, Iraq

How to Cite
Mustafa, R., & Sulaiman, N. A. (2021). A new Mean Deviation and Advanced Mean Deviation Techniques to Solve Multi-Objective Fractional Programming Problem Via Point-Slopes Formula. Pakistan Journal of Statistics and Operation Research, 17(4), 1051-1064. https://doi.org/10.18187/pjsor.v17i4.3789
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References

  1. Akhtar, H., & Modi, G. (2017). An approach for solving multi-objective linear fractional programming problem and it's comparison with other techniques. Intearnational Journal of Scientific and Innovative Mathematical Reasearch (IJSIMR), 5(11).
  2. Akhtar, H., Modi, G., & Duraphe, S. (2017). Transforming and optimizing multi-objective quadratic fractional programming problem. International Journal of Statistics and Applied Mathematics, 2(1), 01-05.
  3. Sen, C. (1983). A new approach for multi-objective rural development planning. The Indian Economic Journal, 30(4), 91-96.
  4. Sen, C. (2018). Sen's multi-objective programming method and its comparison with other techniques. American Journal of Operational Research, 8, 10-13.
  5. Sen, C. (2020). Improved averaging techniques for solving multi-objective optimization (MOO) problems. SN Applied Sciences, 2(2), 1-6.
  6. Sivri, M., Albayrak, I., & Temelcan, G. (2018). A novel approach for solving quadratic fractional programming problems. Croatian Operational Research Review, 9(2), 199.
  7. Sulaiman, N., & Salih, A. (2010). Using mean and median values to solve linear fractional multi objective programming problem. Zanco Journal for pure and applied Science, Salahaddin-Erbil university, 22(5).
  8. Sulaiman, N. A., & Abdulrahim, B. (2013). Using transformation technique to solve multi-objective linear fractional programming problem. International Journal of Research and Reviews in Applied Sciences, 14(3), 559-567.
  9. Sulaiman, N. A., & Mustafa, R. B. (2016a). Transform Extreme Point Multi-Objective Linear Programming Problem to Extreme Point Single Objective Linear Programming Problem by Using Harmonic Mean. Applied Mathematics, 6(5), 95-99.
  10. Sulaiman, N. A., & Mustafa, R. B. (2016b). Using harmonic mean to solve multi-objective linear programming problems. American journal of operations Research, 6(1), 25-30.