Open Access Research Article

Enhancing Possibilistic Fuzzy Goal Programming Approach for Solving Multi Objective Minimum Cost Flow Problems Coefficients

Authors

  • Hamiden Abd El- Wahed Khalifa * Department of Mathematics, College of Science and Arts, Qassim University, Al-Badaya 51951 Saudi Arabia; ‎
  • Seyed Ahmad Edalatanah Department of Applied Mathematics, AyendangInstitute of Higher Education, Tonkabon, Iran

https://doi.org/10.22105/tqfb.v1i1.22

Abstract

This study investigates a multi-objective minimum cost flow with probabilistic objective function coefficients (Poss- MOMCF). Under using the cut set of the possibilistic variables, the Poss-MOMCF problem is converted into the corresponding ( -MOMCF) and hence into the ( -MOMCF) problem. A necessary and sufficient condition for investigating the possibly optimal solution is established. A fuzzy goal programming approach is applied to obtain the parametric optimal compromise solution. The stability set of the first kid under the concept of possibly optimal solution is characterized and analyzed without differentiability. Finally, a numerical example is given in the sake of the paper to clarify the methodology.

Keywords

Optimization problem‎ Minimum cost flow Multi-objective optimization‎ Possibilistic variables‎ Fuzzy goal programming approach‎ α-possibly optimal solution Goal programming Decision maker Compromise solution Parametric analysis
References (32)
  1. [1] ‎[1] ‎ Ahuja, R. K., Magnanti, T., & Orlin, J. (1993). Network Flows. Englewood.‎

  2. [2] ‎[2] ‎ Jewell, W. S. (1957). Warhousing and distribution of a seasonal product 1. Naval research logistics ‎quarterly, 4(1), 29–34. DOI:10.1002/nav.3800040107‎

  3. [3] ‎[3] ‎ Slump, C. H., & Gerbrands, J. J. (1982). A network flow approach to reconstruction of the left ventricle ‎from two projections. Computer graphics and image processing, 18(1), 18–36. DOI:10.1016/0146-‎‎664X(82)90097-1‎

  4. [4] ‎[4] ‎ Sapountzis, C. (1984). Allocating blood to hospitals from a central blood bank. European journal of ‎operational research, 16(2), 157–162. DOI:10.1016/0377-2217(84)90070-5‎

  5. [5] ‎[5] ‎ Hu, Y., Zhao, X., Liu, J., Liang, B., & Ma, C. (2020). An efficient algorithm for solving minimum cost ‎flow problem with complementarity slack conditions. Mathematical problems in engineering, 2020, 1–5. ‎DOI:10.1155/2020/2439265‎

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How to Cite

Abd El- Wahed Khalifa, H. ., & Ahmad Edalatanah, S. . (2024). Enhancing Possibilistic Fuzzy Goal Programming Approach for Solving Multi Objective Minimum Cost Flow Problems Coefficients. Transactions on Quantitative Finance and Beyond, 1(1), 35-47. https://doi.org/10.22105/tqfb.v1i1.22

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