Given a network with a set of nodes and a set of potential edges, we must decide what edges will be included in the design to satisfy demands between pairs of nodes. Each edge has associated a finite capacity, a fixed cost and routing costs. Uncertainty will be considered in important input parameters such as demands and routing costs and will be modeled through scenarios. The objective is to f...

In communication networks (CNs), the uncertainty is caused by the dynamic nature of the traffic demands. Therefore there is a need to incorporate the uncertainty into the network bandwidth capacity design. For this purpose, this paper developed a fuzzy methodology for network bandwidth design under demand uncertainty. This methodology is usually used for offline traffic engineering optimization...

An integrated equilibrium model for tactical decisions in network design is developed. We consider a decentralized supply chain network operating in markets under uncertain demands when there is a rival decentralized chain. The primary assumption is that two chains provide partial substitutable products to the markets, and markets’ demands are affected by tactical decisions such as price, servi...

The aim of this paper is to find solution for route planning in road network for a user, and to find the equilibrium in the path optimization problem, where the roads have uncertain attributes. The concept is based on the Dempster-Shafer theory and Dijkstra's algorithm, which help to model the uncertainty and to find the best route, respectively. Based on uncertain influencing factors an interv...

In this article, a capacitated location allocation problem is considered in which the demands and the locations of the customers are uncertain. The demands are assumed fuzzy, the locations follow a normal probability distribution, and the distances between the locations and the customers are taken Euclidean and squared Euclidean. The fuzzy expected cost programming, the fuzzy β-cost minimizatio...

Intelligent agents are often faced with the need to choose actions with uncertain consequences, and to modify those actions according to ongoing sensory processing and changing task demands. The requisite ability to dynamically modify or cancel planned actions is known as inhibitory control in psychology. We formalize inhibitory control as a rational decision-making problem, and apply to it to ...

In many situations we have to make repeated decisions in an uncertain environment. Those decisions include to choose a route to drive to work, when to refuel a car or when to purchase and sell shares in the stock market. In each of those settings we decide which actions we take, although we do not possess complete information about the situation. Since part of the missing information might infl...

In this research we concentrate on developing a bifuzzy model for a Single-period inventory problem. The conventional studies have focused on the cases that the demands are probabilistic and follow certain distribution function; or the demands are considered as fuzzy variables; or the demands is expressed by random fuzzy variable. Recently, fuzzy random variables have been applied to some decis...

the option-pricing problem is always an important part in modern finance. assuming that the stock diffusion is a constant, some literature has introduced many stock models and given corresponding option pricing formulas within the framework of the uncertainty theory. in this paper, we propose a new stock model with uncertain stock diffusion for uncertain markets. some option pricing formulas on...

in this paper, controlling the gyros with linear plus cubic damping is considered. hence, an adaptive control algorithm is proposed to overcome the uncertainties in model parameters and the chaotic behavior of gyroscopes. it is noted that for general applications dynamic model coefficient of gyros is not precisely determined, on the other hand, with respect to a particular coefficient gyroscope...