In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stochastic linear programming problems, but also multiobjective fuzzy random linear programming problems through a probability maximization model. In a probability maximization model, it is necessary for the decision maker to specify permissible values of objective functions in advance, which have a great infl...

In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stochastic linear programming problems, but also multiobjective fuzzy random linear programming problems through a probability maximization model. In a probability maximization model, it is necessary for the decision maker to specify permissible values of objective functions in advance, which have a great infl...

Decision theory is the contemporary manifestation of the mathematics of the decision process and thus can be viewed as a primary aid to the human decision process. The costs and gains of applying the concepts and algorithms of decision theory are considered in some detail. A man/computer system is described which is designed to make the concepts and algorithms of decision theory available to a ...

In this paper a multi - objective linear fractional programming problem with the fuzzy variables and vector of fuzzy resources is studied and an algorithm based on a parametric approach is proposed. The proposed solving procedure is based on the parametric approach to find the solution, which provides the decision maker with more complete information in line with reality. The simplicity of the ...

The theory of constraints is an approach to production planning and control that emphasizes on the constraints to increase throughput by effectively managing constraint resources. One application in theory of constraints is product mix decision. Product mix influences the performance measures in multi-product manufacturing system. This paper presents an alternative approach by using of goal pro...

the sensitivity analysis for multi-attribute decision making (madm) problems is important for two reasons: first, the decision matrix as the source of the results of a decision problem is inaccurate because it sorts the alternatives in each criterion inaccurately. second, the decision maker may change his opinions in a time period because of changes in the importance of the criteria and in the ...

In existing models of decision under uncertainty where the decision maker may have multiple beliefs (vague beliefs) the different beliefs are not distinguished by their degree of reliability. This paper extends the model of vague beliefs in this direction: the decision maker may have multiple beliefs, but also has a complete order over them (a belief over his own beliefs, or higher order belief...

The multi-armed bandit problem (MBP) is the problem of finding, as accurately and quickly as possible, the most profitable option from a set of options that gives stochastic rewards by referring to past experiences. Inspired by fluctuated movements of a rigid body in a tug-of-war game, we formulated a unique search algorithm that we call the ‘tug-of-war (TOW) dynamics’ for solving the MBP effic...

In this paper, an interactive version of the ParEGO algorithm is introduced for identifying most preferred solutions for computationally expensive multiobjective optimization problems. It enables a decision maker to guide the search with her preferences and change them in case new insight is gained about the feasibility of the preferences. At each interaction, the decision maker is shown a subs...