This paper is the result of an interdisciplinary research between the marketing and the artificial intelligence fields. It briefly presents a brand new methodology to be applied in marketing (causal) modeling. Specifically, we apply it to a consumer behavior model used for the experimentation. The characteristics of the problem (with uncertain data and available knowledge from a marketing exper...

In this paper attention has been paid to the study of multiobjective linear fractional programming problem (MOLFPP) by using fuzzy set theoretic approach. In this approach, MOLFPP is transformed into multiobjective linear programming problem (MOLPP) by suitable transformation. In algorithm-I, MOLFPP is transformed into MOLPP by using fuzzy set theory and the pareto optimal solution of the trans...

When a flexible fuzzy rule structure such as those with antecedent in conjunctive normal form is used, the interpretability of the obtained fuzzy model is significantly improved. However, some important problems appear related to the interaction among this set of rules. Indeed, it is relatively easy to get inconsistencies, lack of completeness, redundancies, etc. Generally, these properties are...

We focus on multiobjective nonlinear integer programming problems with block-angular structures which are often seen as a mathematical model of large-scale discrete systems optimization. By considering the vague nature of the decision maker’s judgments, fuzzy goals of the decision maker are introduced, and the problem is interpreted as maximizing an overall degree of satisfaction with the multi...

The purpose of the paper is to introduce a new type of fuzzy matrix games: fuzzy constrained matrix games. A computational method for its solution based on establishment of the auxiliary fuzzy linear programming for each player is proposed. The approach based on the multiobjective programming is established to solve these fuzzy linear programming. Effectiveness is illustrated with a numerical e...

This paper presents a method to solve a linear or nonlinear Fuzzy Multiobjective Programming problem. We propose Genetic Search based approaches to the case in which fuzzy constraints are assumed.

This paper considers multiobjective linear programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed by incorporating the concept of fractile criteria optimization into a possibilistic programming model. An interactive fuzzy satisficing method is presented for deriving a satisficing solution for a deci...

In this paper, we demonstrate that simple fuzzy rule-based classification systems with high interpretability are obtained through multiobjective genetic rule selection. In our approach, first a prespecified number of candidate fuzzy rules are extracted from numerical data in a heuristic manner using rule evaluation criteria. Then multiobjective genetic rule selection is applied to the extracted...