Customers often have various requirements and preferences on a product. A product market can be partitioned into several market segments, each of which contains a number of customers with homogeneous preferences. In this paper, a methodology which mainly involves a market survey, fuzzy clustering, quality function deployment (QFD) and fuzzy optimization, is proposed to achieve the optimal targe...

The decision data of human judgments with preferences are often vague in many real life cases. Human judgments with preferences are often unclear and hard to estimate by exact numerical values. So that the traditional ways of using crisp values are inadequate. The relationship among criteria and choosing and rating alternatives based on criterion are often expressed in terms of linguistic terms...

This paper presents an agent-based fuzzy constraintdirected negotiation mechanism for planning and scheduling in supply chain. The supply chain scheduling problem is modeled as a set of fuzzy constraint satisfaction problems (FCSPs), interlinked together by inter-agent constraints. For converging each distinct firm’s interests, the conflicts among the set of FCSPs are resolved through negotiati...

The idea of introducing preferences into queries is gaining more and more attention in the database community. After some initial works in the 1970s and 1980s, such as nearest neighbors (Friedman, Baskett, & Shustek, 1975), Deduce2 (Chang, 1982), Preferences (Lacroix & Lavency, 1987), Ares (Ichikawa & Hirakawa, 1986), and Vague (Motro, 1988), a new stream of work, including top-k queries (Bruno...

This paper presents a flexible querying system of fuzzy RDF annotations which consists in translating fuzzy RDF annotations into fuzzy conceptual graphs and using an “approximate”-projection operation in order to compare fuzzy query graphs with fuzzy annotation graphs. The fuzzy sets in the query graphs having a semantic of preferences are compared with the fuzzy sets in the annotation graphs h...

Most of the researches in the domain of fuzzy number comparisons serve the fuzzy number ordering purpose. For making a comparison between two fuzzy numbers, beyond the determination of their order, it is needed to derive the magnitude of their order. In line with this idea, the concept of inequality is no longer crisp however it becomes fuzzy in the sense of representing partial belonging or de...

Since much of human reasoning is based on imprecise, vague and subjective values, most of decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Zadeh’s (Zadeh 1965) fuzzy logic has given analysts a tool to represent the human behaviour more precisely, especially where relatively few data exist, and where the expert knowledge about the system is vague and lin...

Hierarchical structures and uncertainty measures are two main aspects in granular computing, approximate reasoning and cognitive process. Typical hesitant fuzzy sets, as a prime extension of fuzzy sets, are more flexible to reflect the hesitance and ambiguity in knowledge representation and decision making. In this paper, we mainly investigate the hierarchical structures and uncertainty measure...

Preferences and uncertainty occur in many real-life problems. We are concerned with the coexistence of preference and uncertainty in the same problem. In particular, we consider uncertainty, defined by the theory of possibility [2], that is one non-probabilistic way of dealing with uncertainty, that comes from lack of data or imprecise knowledge. We propose a method to integrate fuzzy preferenc...

We present a new framework for modelling users preferences in a fuzzy setting. Starting with a formal fuzzy context, the user enters so-called attribute dependency formulas based on his priorities. The method then yields the “interesting” formal concepts, that is, interesting from the point of view of the user. Our approach is designed for compounded attributes, i.e., attributes which include m...