this paper studies a new multi-objective fuzzy optimization prob- lem. the objective function of this study has dierent levels. therefore, a suitable optimized solution for this problem would be an optimized solution with preemptive priority. since, the feasible domain is non-convex; the tra- ditional methods cannot be applied. we study this problem and determine some special structures related...

This research article aims to study a multi-objective linear fractional programming (FMOLFP) problem having fuzzy random coefficients as well pseudorandom decision variables. Initially, the FMOLFP model is converted single objective (FLP) model. Secondly, we show that optimal solution of an FLP resolved into class relative (LP) As result, some theorems LP combined with series solutions problems...

in this paper, we show that inverse data envelopment analysis (dea) models can be used to estimate output with fuzzy data for a decision making unit (dmu) when some or all inputs are increased and deficiency level of the unit remains unchanged.

One of the main challenges designing effective reverse logistic network is to predict amount product which reach end their useful life. Thus, in this study, we propose fuzzy multi-objective mixed integer linear programming (Fuzzy-MOMILP) model returned considered as an uncertain parameter. In order solve proposed multi objective mathematical model, a solution approach applied. The Fuzzy-MOMILP ...

The traditional frameworks for fuzzy linear optimization problems are inspired by the max–min model proposed by Zimmermann using the Bellman–Zadeh extension principle to aggregate all the fuzzy sets representing flexible (fuzzy) constraints and objective functions together. In this paper, we propose an alternative approach to model fuzzy multi-objective linear programming problems (FMOLPPs) fro...