the bi-objective warehouse problem in a crisp environment is often not eective in dealing with the imprecision or vagueness in the values of the problem parameters. to deal with such situations, several researchers have proposed that the parameters be represented as fuzzy numbers. we describe a new algorithm for fuzzy bi-objective warehouse problem using a ranking function followed by an applic...

fuzzy measures are suitable in analyzing human subjective evaluation processes. several different strategies have been proposed for distance of fuzzy numbers. the distances introduced for fuzzy numbers can be categorized in two groups:1. the crisp distances which explain crisp values for the distance between two fuzzy numbers.2. the fuzzy distance which introduce a fuzzy distance for normal fuz...

artificial neural networks (anns) are flexible computing frameworks and universal approximators that can be applied to a wide range of time series forecasting problems with a high degree of accuracy. however, despite of all advantages cited for artificial neural networks, they have data limitation and need to the large amount of historical data in order to yield accurate results. therefore, the...

the planning of production and control of inventory problem is one of most important problems that companies are face with them. some times inattention to uncertainty in these problems causes to increase of costs of inventory control systems. one of the important ways encountering to uncertainty is the widespread of fuzzy sets instead of crisp numbers because in this approach, we can determine ...

this paper proposes a new mathematical model for the integrated procurement-production-distribution problem of a fuzzy mixed integer linear programming (fmilp) type. considering the uncertainty in real problems, a number of parameters such as demand, capacity, and cost where their values are not available or known precisely, have been considered as trapezoidal fuzzy numbers. to solve fuzzy mixe...

In this paper, we first use a fuzzy preference relation with a membership function representing preference degree forcomparing two interval-valued fuzzy numbers and then utilize a relative preference relation improved from the fuzzypreference relation to rank a set of interval-valued fuzzy numbers. Since the fuzzy preference relation is a total orderingrelation that satisfies reciprocal and tra...

we use the basic binomial option pricing method but allow someor all the parameters in the model to be uncertain and model this uncertaintyusing fuzzy numbers. we show that with the fuzzy model we can, with areasonably small number of steps, consider almost all possible future stockprices; whereas the crisp model can consider only n + 1 prices after n steps.