By fuzzifying the number of occurrences of an element of a multiset, we obtain a new fuzzy structure; similarly, by fuzzifying the number of occurrences of an element of a hybrid set, we obtain another new fuzzy structure. The aim of the present work is twofold: to provide a concise definition of these new fuzzy structures and their properties and to apply them in natural computing. More specif...

For a fixed finite universe U = {u1, . . . , un}, a fuzzy subset F of U is given by its membership function F : U → [0, 1] (we will not distinguish fuzzy subsets and the corresponding membership functions notations). For several practical purposes, especially in multicriteria decision making, the expected value E(F ) of F should be introduced. The original Zadeh approach in [11] was based on a ...

uncertainty inherent in the financial market was usually consid- ered to be random. however, randomness is only one special type of uncer- tainty and appropriate when describing objective information. for describing subjective information it is preferred to assume that uncertainty is fuzzy. this paper defines the expected payoof trading strategies in a fuzzy financial market within the framewor...

Fuzzy set has been applied in many real applications to handle uncertainty. The aim of the paper is to study the replacement problem with uncertainty. This problem involves capital cost, scrap value or salvage value, maintenance cost or operating cost, and rate of interest having an imprecise value. Here, we assume the imprecise values as positive trapezoidal fuzzy numbers. Moreover, we conside...

In fuzzy decision systems, we model insuring critical path problem by two-stage risk-aversion fuzzy programming. For the proposed two-stage insuring critical path problem, we first define three solution concepts, expected value solution, wait-and-see solution and here-and-now solution, then introduce the value of perfect information of value-at-risk (VaRVPI) and the value of the fuzzy solution ...

Recently, Zhao et al. [Fuzzy Optimization and Decision Making (2007) 6, 279-295] characterized the interarrival times as fuzzy random variables and presented a fuzzy random elementary renewal theorem on the limit value of the expected renewal rate of the process in the fuzzy random renewal process. They also depicted both the interarrival times and rewards are depicted as fuzzy random variables...

This paper presents an online tuning strategy for model predictive control. Specifically, the tuning strategy adjusts automatically the prediction horizon, P, the diagonal elements of the input weight matrix, Λ, and the diagonal elements of the output weight matrix, Γ. The control horizon is left constant because its relative value with respect to P is more important. The MPC parameters are adj...