The Development of A Syemmetrical Fuzzy Stochastic Multi-Objective Linear Program and Its Solution using Chance Constrained Technique

  • Grandianus Seda Mada Universitas Timor
Keywords: Symmetrical Model, MOFSLP-SODLP, Chance Constrained Technique


Linear programming is one method oto determine the optimum value of a problem. Problems of the linear program faced by the decision makers have various variations from time to time. A variety of problems that can be seen as a multi-objective fuzzy linear programming, muli-objective stochastic linear programming, or a combination of both. This study focus on Multi-Objective Fuzzy Stochastic Linear Programming (MOFSLP) with each objective function has a same level of importance for decision makers or name as symmetrical model. The objective function of the MOFSLP contains the fuzzy parameters and normally distributed random variables while the function of constraints contains the fuzzy parameters. The purpose of this research is to formulate MOFSLP and develop algorithms to transform MOFSLP be Single-Objective Deterministic Linear Programming (SODLP) which can be solve using the simplex method. In transforming MOFSLP to SODLP, symmetrical model and also the chance constrained technique are used. In the end of this research, a numerical example is provided to illustrate the algorithm that has been developed. The models and algorithms that have been formed are expected to help decision makers in solving a problem.


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Amid, A., Ghodsypour, S. H., O’Brien, C. 2006. Fuzzy multiobjective linear model for supplier selection in a supply chain. International Journal of Production Economics, 104(2), 394–407.

Balan, B. T. 2016. Solving Multi-Objective Fuzzy Linear Optimization Problem Using Fuzzy Programming Technique. IOSR Journal of Mathematics, 4.

Cheng, H., Huang, W., Zhou, Q., Cai, J. 2013. Solving fuzzy multi-objective linear programming problems using deviation degree measures and weighted max–min method. Applied Mathematical Modelling, 37(10–11), 6855–6869.

Hulsurkar, S., Biswal, M. P., Sinha, S. B. 1997. Fuzzy programming approach to multi-objective stochastic linear programming problems. Fuzzy Sets and Systems, 88(2), 173–181.

Kalaichelvi, D. A., Janofer, K. 2012. α-Cuts Of Triangular Fuzzy Numbers And Α-Cuts Of Triangular Fuzzy Number Matrices. Int Jr. of Mathematics Sciences & Applications, 2 (2), 655-645.

Mada, G. S. 2019. Model Pembobotan Aditif Termodifikasi Untuk Menyelesaikan Masalah Pemilihan Supplier Multi-Objektif Fuzzy dengan Fungsi Objektif Fuzzy Dan Kendala Fuzzy Pada Rantai Supply. Prosiding Seminar Nasional Sainstek IV Universitas Nusa Cendana Kupang, 25 Oktober 2019.

Nehi, H. M., Alineghad, M. (2008). Solving Interval and Fuzzy Multi Objective Linear Programming Problem by Necessarily Efficiency Points. 8.

Ramík, J., Rimanek, J. 1985. Inequality relation between fuzzy numbers and its use in fuzzy optimization. Fuzzy Sets and Systems, 16(2), 123–138.

Sakawa, M. 1993. Fuzzy Sets and Interactive Multiobjective Optimization. Springer US.
How to Cite
Mada, G. (2022). The Development of A Syemmetrical Fuzzy Stochastic Multi-Objective Linear Program and Its Solution using Chance Constrained Technique. Jurnal Saintek Lahan Kering, 4(2), 22-24.
Original research article