Abstract Inducing information and bi-polar preference-based weights allocation relevant decision-making are one important branch of Yager’s decision theory. In the context basic uncertain environment, there exist more than inducing factor relative importance between them should be determined. Some subjective methods require makers to indicate preference extents for each as well all involved fac...

The management of a controllable production in the manufacturing system is essential to achieve viable advantages, particularly during emergency conditions. Disasters, either man-made or natural, affect and supply chains negatively with perilous effects. On other hand, flexibility resilience manage perpetuated risks are vital for achieving rate. Still, these performances strongly dependent on m...

Many decision problems can be formulated as the problem of minimising a convex cost function that also depends on an uncertain variable. In this seminar, we take a databased approach to deal with uncertainty. We will focus mainly on a worst-case approach, where we minimise the maximum of the cost functions corresponding to some previously observed instances of the uncertain variable. We call th...

Abstract A discrete variable structure control methodology is presented to suppress vibration of high-speed flexible parallel robot. The elastic dynamic model of the flexible robot is built by using the finite element method and experimental modal testing. Considering uncertain external disturbances and measurement noise, and uncertain parameters of the system, we can utilize invariance of the ...

In this paper, we study the linear fractional transportation problem with uncertain arameters. After recalling some definitions, concepts and theorems in uncertainty theory we present three approaches for solving this problem. First we consider the expected value of the objective function together with the expectation of satisfying constraints. Optimizing the expected value of the objective fun...

This paper presents a strategy for optimal design of chemical processes with stochastic uncertain parameters defined inside bounded intervals. Strategy relies on approximate stochastic optimization at one single point, called the central basic point (CBP), while desired flexibility is achieved by simultaneous consideration of critical points. The CBP method has been extensively described elsewh...

We demonstrate here a method for the verified solution of nonlinear ODE models in physiology, computing rigorous bounds on the trajectories of the state variables, based on the ranges of the uncertain parameters. We also demonstrate an approach for the propagation of uncertain probability distributions in one or more model parameters and/or initial conditions. Assuming an uncertain probability ...

A complex structure has many uncertain factors and how to make a more accurate analysis on the structure reliability by a method is the key in engineering calculation. Rough set theory is utilized to analyze the fuzzy, random and uncertain factors and upper and lower approximation set relation is used to calculate the value taking interval of reliability index to make reliability index analysis...