Pengembangan Program Linear Multi-Objektif Fuzzy Stokastik Model Simetris dan Penyelesaiannya dengan Menggunakan Teknik Chance Constrained - Grandianus Seda Mada; Ernestina Lalian; Faustianus Luan; Eva Binsasi (Fakultas Pertanian, Universitas Timor, 2021)
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.