A method for incorporating fuzzy preferences into evolutionary multiobjective optimization is proposed. After introducing three commonly used models for describing fuzzy preferences, a method to convert fuzzy preferences into realvalued weight intervals is suggested. It is argued that to convert fuzzy preferences into interval-based weights is more consistent with the motivation of using fuzzy ...

We present a unified logical framework for representing and reasoning about both quantitative and qualitative preferences in fuzzy answer set programming [Saad, 2010; Saad, 2009; Subrahmanian, 1994], called fuzzy answer set optimization programs. The proposed framework is vital to allow defining quantitative preferences over the possible outcomes of qualitative preferences. We show the applicat...

We propose a model of a middleware system enabling personalized web search for users with different preferences. We integrate both inductive and deductive tasks to find user preferences and consequently best objects. The model is based on modeling preferences by fuzzy sets and fuzzy logic. We present the model-theoretic semantics for fuzzy description logic f-EL which is the motivation of creat...

We propose a model of a middleware system enabling personalized web search for users with different preferences. We integrate both inductive and deductive tasks to find user preferences and consequently best objects. The model is based on modeling preferences by fuzzy sets and fuzzy logic. We present the model-theoretic semantic for fuzzy description logic f-EL which is the motivation of creati...

This paper presents a mathematical model for dynamic decision making with an objective function induced from fuzzy preferences. The fuzzy preference is related to decision making in artificial intelligence, and this paper models human behavior based on his fuzzy preferences. A reasonable criterion based on fuzzy preferences is formulated for the dynamic decision making, and an optimality equati...

The fuzzy preference framework of Graph Model for Conflict Resolution (GMCR), handling both crisp and fuzzy preferences of decision makers (DMs), is capable of calculating and predicting different conflict resolutions (equilibria) according to DMs’ different satisficing criteria. Employing this methodology, a water contamination conflict occurs at the boundary of Jiangsu and Zhejiang provinces ...

A conflict analysis framework with fuzzy preference can be utilized to model and analyze conflicts in which decision makers (DMs) hold unclear or ambiguous preferences. One important function of this framework is that it can predict different conflict resolutions based on DMs’ different fuzzy satisficing thresholds. The fuzzy preference conflict analysis framework extends the option prioritizat...

In this article, we propose a method to deal with incomplete interval-valuedhesitant fuzzy preference relations. For this purpose, an additivetransitivity inspired technique for interval-valued hesitant fuzzypreference relations is formulated which assists in estimating missingpreferences. First of all, we introduce a condition for decision makersproviding incomplete information. Decision maker...