System reliability optimization is often faced with imprecise and conflicting goals such as reducing the cost of the system and improving the reliability of the system. The decision making process becomes fuzzy and multi-objective. In this paper, we formulate the problem as a fuzzy multi-objective nonlinear program (FMOOP). A fuzzy multiobjective genetic algorithm approach (FMGA) is proposed fo...

This paper proposes a compromise model, based on a new method, to solve the multi-objective large-scale linear programming (MOLSLP) problems with block angular structure involving fuzzy parameters. The problem involves fuzzy parameters in the objective functions and constraints. In this compromise programming method, two concepts are considered simultaneously. First of them is that the optimal ...

FUZZY LINEAR PROGRAMMING USING MULTIATTRIBUTE VALUE FUNCTION Masahiro INUIGUCHI Hidetomo ICHIHASHI Hideo TANAKA University of Osaka Prefecture In this paper, a fuzzy linear programming problem is formulated under the assumption that a multiattribute value function is given, and its method of solution is proposed. The fuzzy linear programming problem in this paper is the unconstrained linear pro...

Within the multicriteria aggregation-disaggregation framework, ordinal regression aims at inducing the parameters of a decision model, for example those of a utility function, which have to represent some holistic preference comparisons of a Decision Maker (DM). Usually, among the many utility functions representing the DM’s preference information, only one utility function is selected. Since s...

We propose Fuzzy UTASTAR, a method for inferring fuzzy utility functions from a partial preorder of options evaluated on multiple criteria. It is an extension of the well-known UTASTAR method capable to handle both ordinary (crisp) and fuzzy evaluation data. This property gives much flexibility to decision makers because the majority of real-life decision problems involve a considerable level o...

This paper proposes a compromise model, based on a new method, to solve the multiobjectivelarge scale linear programming (MOLSLP) problems with block angular structureinvolving fuzzy parameters. The problem involves fuzzy parameters in the objectivefunctions and constraints. In this compromise programming method, two concepts areconsidered simultaneously. First of them is that the optimal alter...

The concept of utility is used as a decision tool for consumers to choose a commodity. Analyzing consumer behavior is complicated due to the qualitative nature of the utility. Hence, this paper investigates a quantitative method to evaluate the utility of consumers. The methodology is based on linguistic expressions of fuzzy logic. Initially, the authors identify different parameters being effe...

We revisit the notion of fuzzy revealed preference, with the intention of using it in decision making. A decision making agent manages resources that are priced, and it has a certain wealth. We review proposed fuzzifications of preference relations. Although they are well founded, they cannot deal well with decision making under fuzzy constraints. We introduce the fuzzy budget set as a general ...

Conventional Frequent pattern mining discovers patterns in transaction databases based only on the relative frequency of occurrence of items without considering their utility. Until recently, rarity has not received much attention in the context of data mining. For many real world applications, however, utility of itemsets based on cost, profit or revenue is of importance. Most Association Rule...