a common problem arising in project management is the fact that the baseline schedule is often disrupted during the project execution because of uncertain parameters. as a result, project managers are often unable to meet the deadline time of the milestones. robust project scheduling is an effective approach in case of uncertainty. upon adopting this approach, schedules are protected against po...

representation and modeling of economic uncertainty is addressed by different modeling methods, namely stochastic variables and probabilities, interval analysis, and fuzzy numbers, in particular triple estimates. fo-cusing on discounted cash flow analysis numerical results are presented, comparisons are made between alter-native modeling methods, and characteristics of the methods are discussed.

many constants and coefficient effect on the modeling results. in many cases, it is possible these constants and coefficients differ from their real values in the environment, but the modeling results adapted with real boundary conditions due to other factors adjustment during modeling. uncertainty analysis is a tool for assessing the effect of uncertainty of various factors on the modeling res...

Representation and modeling of economic uncertainty is addressed by different modeling methods, namely stochastic variables and probabilities, interval analysis, and fuzzy numbers, in particular triple estimates. Fo-cusing on discounted cash flow analysis numerical results are presented, comparisons are made between alter-native modeling methods, and characteristics of the methods are discussed.

in this paper, we present the stochastic version of maximal covering location problem which optimizes both location and allocation decisions, concurrently. it’s assumed that traveling time between customers and distribution centers (dcs) is uncertain and described by normal distribution function and if this time is less than coverage time, the customer can be allocated to dc. in classical model...

in today's dynamic and uncertain environment, knowledge is a strategic source for organizations to gain the competitive advantage and innovation. in this research, we have investigated mediating role of knowledge management between environmental uncertainty and organizational innovation. data was collected through questionnaire from 89 large and medium sized manufacturing companies in suburb ma...

a central aim of educational research in the area of mathematical modeling and applications is to recognize the attainment level of students at defined states of the modeling process. in this paper, we introduce principles of fuzzy sets theory and possibility theory to describe the process of mathematical modeling in the classroom. the main stages of the modeling process are represented as fuzz...

truncated gaussian simulation (tgs) is a well-known method to generate realizations of the ore domains located in a spatial sequence. in geostatistical framework geological domains are normally utilized for stationary assumption. the ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. as a simple a...