Decision-making In Fuzzy Environment Research Articles

Evaluation of Strategic Information Security with Fuzzy AHP Method

Successful e-government adoption in society depends mostly on trust among citizens who use it. It is vital to ensuring security of e-government applications and infrastructures as a guarantee of security and privacy of stakeholders in storing, processing and exchanging information over the online systems offered by the government. As threats on e-government information security are dynamic and continue to grow, policy makers need to perform evaluation on existing information security strategy to establish a trusted e-government service. This paper intends to propose a new method that can guide decision makers in evaluating strategic government information security. The evaluation framework is based on new Fuzzy Analytic Hierarchy Process that combines tangible and intangible factors as well as has specific capabilites to be used in vague and fuzzy decision environment which is common in information security related issues.

Intuitionistic Fuzzy QUALIFLEX Method for Optimistic and Pessimistic Decision Making

Intuitionistic fuzzy sets are suitable for capturing imprecise or uncertain decision information in multiple criteria decision analysis. In addition, optimism and pessimism generally affect the manner in which subjective judgments are construed. This paper proposes an outranking model, a QUALIFLEX method, for relating optimism and pessimism within the intuitionistic fuzzy decision environment. This paper treats the influences of optimism and pessimism differently by using the unipolar bivariate model. In addition, the proposed method investigates all possible permutations of alternatives with respect to the consequences of all criteria. A ranking procedure is employed to compare intuitionistic fuzzy values by using the inclusion comparison probability.

Intuitionistic Fuzzy Decision Analysis with Dissonance Reduction For Optimistic/Pessimistic Decision Makers

The theory of Atanassov's intuitionistic fuzzy sets has been developed and has been successfully applied in the field of multiple criteria analysis. However, there is a lack of information about the role of optimism and pessimism on subjective judgments and cognitive dissonance accompanying the decision process. This paper presents a new method of reducing cognitive dissonance and relating optimism and pessimism to multiple criteria decision analysis under Atanassov's intuitionistic fuzzy decision environment. We utilize optimistic and pessimistic point operators to measure the effects of optimism and pessimism, respectively, and further determine the suitability function through weighted score functions. Considering two objectives of maximal suitability and dissonance reduction, several optimization models are constructed to obtain optimal weights for criteria and to acquire the corresponding suitability degree for alternative rankings. We anticipate that the proposed method will give insight into the influences of optimism, pessimism, and cognitive dissonance on decision analysis.

A fuzzy AHP approach based on the concept of possibility extent

The main purpose of this paper is to develop a fuzzy AHP method for tackling the uncertainty and imprecision existing in multi-criteria decision process. The proposed method uses fuzzy pair-wise comparison judgments in place of exact numerical values of the comparison ratios. The geometric mean technique is used to integrate all decision-makers’ opinions and construct the fuzzy positive reciprocal matrices. The algebraic operations of triangular fuzzy numbers are utilized to calculate the fuzzy suitability indices of all alternatives. The extent analysis method is used to compute the degree of possibility of priority among fuzzy suitability indices. Besides, two principles are presented to solve the multi-criteria decision problem in a fuzzy decision environment. Principle I provides a partial preorder, and Principle II gives a total preorder on the set of the possible alternatives. Finally, a numerical example of selecting the company with optimal performance in performing customer relationship management is used to demonstrate the decision process of proposed method.

Optimistic and pessimistic decision making with dissonance reduction using interval-valued fuzzy sets

Interval-valued fuzzy sets have been developed and applied to multiple criteria analysis. However, the influence of optimism and pessimism on subjective judgments and the cognitive dissonance that accompanies the decision making process have not been studied thoroughly. This paper presents a new method to reduce cognitive dissonance and to relate optimism and pessimism in multiple criteria decision analysis in an interval-valued fuzzy decision environment. We utilized optimistic and pessimistic point operators to measure the effects of optimism and pessimism, respectively, and further determined a suitability function through weighted score functions. Considering the two objectives of maximal suitability and dissonance reduction, several optimization models were constructed to obtain the optimal weights for the criteria and to determine the corresponding degree of suitability for alternative rankings. Finally, an empirical study was conducted to validate the feasibility and applicability of the current method. We anticipate that the proposed method can provide insight on the influences of optimism, pessimism, and cognitive dissonance in decision analysis studies.

An outcome-oriented approach to multicriteria decision analysis with intuitionistic fuzzy optimistic/pessimistic operators

The concept of Atanassov’s intuitionistic fuzzy sets is a generalization of ordinary fuzzy sets. Under the intuitionistic fuzzy decision environment, this paper develops optimistic and pessimistic point operators to draw the influences of optimism and pessimism on multiple criteria decision analysis. We propose the optimistic and pessimistic score functions based on point operators to measure evaluations of the alternative with respect to each criterion. The suitability function can then be established to determine the degree to which the alternative satisfies the decision maker’s requirement. An optimization model with suitability functions is propounded on account of ill-known membership grades to generate optimal weights for criteria. Finally, an outcome-oriented approach is adopted to validate the proposed methods. Several multiattribute evaluation cases in consumer decision making reality are addressed to examine the feasibility and applicability of the current method. From the empirical results of effectiveness examination, the proposed intuitionistic fuzzy multicriteria decision making method with optimistic/pessimistic score functions performed significantly better than the method without consideration of optimism/pessimism. Therefore, we can conclude that the proposed methods by using intuitionistic fuzzy optimistic/pessimistic point operators have desirable potentials in practice.

The Cournot game under a fuzzy decision environment

The conventional precision-based decision analysis methodology is invalid for business decision analysis when precise assessment data seldom exist. This paper considers the Cournot game with fuzzy demand and fuzzy costs that are assumed to be triangular fuzzy numbers. Our model utilizes the weighted center of gravity (WCoG) method to defuzzify the fuzzy profit function into a crisp value. We derive the equilibrium Cournot quantity of each firm by simultaneously solving the first-order condition of each firm. Our model explicitly derives the necessary condition to avoid an unreasonable outcome of negative equilibrium quantities and lack of flexibility for modification of the ranking method. In addition, we examine the standard deviation of the fuzzy profit resulting from the fuzziness of each firm’s cost and market demand functions. We conduct sensitivity analysis to investigate the effect of parameter perturbations on firms’ outcomes. The results indicate that the center of parameter plays an important role in sensitivity analysis and dominates over variations in equilibrium quantity due to a perturbation of fuzzy parameters.

The optimum output quantity of a duopoly market under a fuzzy decision environment

The main purpose of this paper is to develop a new optimum output quantity decision analysis of a duopoly market under a fuzzy decision environment. To efficiently handle the fuzziness of the decision variables, the linguistic values, subjectively represented by the trapezoidal fuzzy numbers, are used to act as the evaluation tool of decision variables such as fixed cost and unit variable cost. This paper will apply fuzzy set theory to construct an optimum output quantity decision model based on aiming for the maximum profit of a duopoly market. By using this decision model, the decision-makers’ fuzzy assessments with various variables can be considered in the decision process to assure more convincing and accurate decision-making.

An approach to stopping problems of a dynamic fuzzy system

We formulate a stopping problem for dynamic fuzzy systems concerning with fuzzy decision environment. It could be regarded as a natural fuzzification of non-fuzzy stopping problem with a deterministic dynamic system. The validity of the approach by α-cuts of fuzzy sets will be discussed in constructing One-step Look Ahead policy of an optimal fuzzy stopping time. A numerical example is given to illustrate the theoretical results and to show a merit to use fuzzy stopping times in dynamic fuzzy systems.

An optimistic decision-making in fuzzy environment

Bellman and Zadeh have originated three systems of multistage decision processes in a fuzzy environment: deterministic, stochastic and fuzzy systems. In this article, we consider an optimization problem with an optimistic criterion on a fuzzy system. By making use of minimization–maximization expectation in a fuzzy environment, we derive a recursive equation for the fuzzy decision process through invariant imbedding approach. By illustrating a three-state, two-decision and two-stage model, we give an optimal solution through dynamic programming. The optimal solution is also verified by the method of multistage fuzzy decision tree-table.

Conditional decision-making in fuzzy environment

Recently regular (unconditional) decision has been mathematically formulated from the multistage decision in Bellman and Zadeh's paper Decision-making in fuzzy environment. According to the available information on total fuzziness, we propose two types of conditional decision for regular decision One is an a posteriori conditional decision process and the other is an a priori conditional decision process. The posteriori is formulated through taking at each stage backward conditional expectation of remaining after performing take-action for the regular decision The priori is through taking at each stage backward conditional expectation before take-action. We derive recursive equations for both posteriori and priori processes with numerical illustrations.

Timber harvest scheduling in a fuzzy decision environment

Linear programming is a widely used tool for timber harvest scheduling in North America. However, some potential problems related to infeasible harvest schedules, overly optimistic objective function values, and the need to strictly satisfy all constraints included in deterministic model formulations have been raised. This paper describes a fuzzy approach for explicitly recognizing the imprecise nature of the harvest flow constraints usually included in harvest scheduling models. The objective function and selected constraints are viewed as soft, and satisfactory solutions are derived and discussed for several scenarios. An illustrative sample problem is presented to demonstrate the methodology, and a comparison with solutions derived from a traditional linear programming model is presented.