[PDF] Top 20 Random Fuzzy Multiobjective Linear Programming Through Probability Maximization

... Considering the imprecise nature of the decision maker’s judgment, we assume that the decision maker has a fuzzy goal for each permissible objective level. Such a fuzzy goal can be quantified by eliciting ... See full document

... a probability maxi- mization model or a fractile optimization model is adopted in order to deal with ...permissible probability levels ...has fuzzy goals ... See full document

... on multiobjective fuzzy random programming problems with simple recourse through a fractile optimization model, in which fuzzy random variables coefficients are involved ... See full document

... hierarchical multiobjective stochastic linear programming problems to obtain a satisfactory solution from among a Pareto optimal solution ...permissible probability levels, the corresponding ... See full document

... stochastic programming approaches have been proposed to deal with mathematical programming problems with random variable ...two-stage programming methods and the other is chance constraints ... See full document

... of fuzzy random variable constraint coefficients defined on a probability space (Q, 2°, P ...Deterministic Linear Programming (SDLP) ... See full document

... Ranking fuzzy number is used in decision- making process in an economic ...In fuzzy environment ranking fuzzy numbers is a very important decision making ...of fuzzy set was first proposed by ... See full document

... hierarchical multiobjective stochastic linear programming problems, and propose an interactive algorithm to obtain a satisfactory solution from among a Pareto optimal solution ...permissible ... See full document

... optimization, probability theory and multicriteria decision analysis are interwoven to address situations where the presence of several objective functions and the stochastic nature of data are under one roof in a ... See full document

... Consequently, probability and possibility theories are widely used as it is capable to treat the random and fuzzy information ...respectively. Fuzzy sets [1] play a significant role and are ... See full document

... In multiobjective stochastic programming problems, it is implicitly assumed that uncertain parameters or co- efficients can be expressed as random variables in prob- ability ...of random ... See full document

... of fuzzy approaches are proposed for not only multiobjective stochastic linear program- ming problems, but also multiobjective fuzzy random linear programming ... See full document

... stochastic programming approaches [1], [2], [3], [6] and fuzzy pro- gramming approaches [12], [14], [25] have been ...mathematical programming problems with fuzzy random variables [11] ... See full document

... In such a turbulent environment the notion of “opti- mum optimorum” is not clearly defined and satisficing rather than optimal search behavior seems to be the most appropriate option. A look at the literature reveals ... See full document

... a linear programming problem with homogeneous constraints in fuzzy ...introduced fuzzy linear programming problem with fuzzy homogeneous constraints Al and Thangaraj ... See full document

... It measures the distance between a pair of closed ele- ments of . A smaller number of points, a lower cov- erage error and a more uniform level are desirable in order to have a good representation of the efficient set. ... See full document

... of fuzzy set theory in [3], people have realized that like to have a decision which not only makes as much profit as possible, but also avoids as much risk as ...nonlinear programming problems ... See full document

... of random closed set and fuzzy random variable and we briefly discuss some of their ...of fuzzy random variables can be embedded into the set of random closed sets isomorphically ... See full document

... intuitionistic fuzzy optimization techniquefor non-linear membership ...intuitionistic fuzzy optimization provides better results than fuzzy ... See full document

... presentsa multiobjective linear programming (MOLP) model in which the cost coefficients of each decision variable of the objective functions aremodeledin weighted intervals and there exists a minimum ... See full document