simulation model

Processes are one of the main foundations of the Information Technology Infrastructure Library, and their security is necessary to support the goals effectively. Also, the rapid progress of the Internet of Things in all fields has made it possible to expand it. Analyzing and providing innovative programs and smart solutions to increase the quality of security by harmonizing the goals with the current situation and modifying and improving it is one of the pillars of this research. Analysis of relationships is one of the important factors for the security of processes to meet the security requirements of IoT, ITIL, tools, models, and methods. Four domains and three phases of public, private, and publishing security in three free, academic, and organizational categories with attack scenarios, levels, probability of attacks, parameters, equations, and flow rates are considered in the simulation model. The parameter change test analyzes and confirms the simulation model and manual models. In the next step, the calibration test is performed, and the optimal values are included in the simulation model.

Earned Value Management (EVM) is known as an efficient and well-known tool for project management. Examining various sources, it was observed that although the EVM analytical model has introduced good indicators for measuring project progress, it is weak in estimating the final cost of the project and does not predict the process of cost change and project efficiency. On the other hand, nothing has been done so far to use system dynamics in EVM.Therefore, considering the capacity of system dynamics in modeling complex systems and setting parameters dynamically based on model variables, the main problem of modeling research is the value model obtained by simulating system dynamics. The dynamic hypothesis of the research was that there are dynamics between the main indicators of EVM. Identifying these dynamics and the way they affect each other can lead to estimating the process of changing costs and project efficiency by the end of the project.Through presenting the causal loop diagram and the stack flow diagram of the proposed model, the variables were determined and after simulation, the model was validated by performing various tests and different policy scenarios were presented.The comparison of the results of the research simulation model with the results of the EVM analytical model revealed that there is a slight difference between the results and the efficiency. The main contribution of the research is the creation of a simulation model based on system dynamics as the core of the simulation to estimate the trend and the final amount of efficiency and cost of the project, which can be part of a more comprehensive simulation model.This can be used to determine the impact of various project management functions on improving project efficiency, which is the main suggestion for further research.

This article proposes composition of fuzzy sets theory with discrete-event simulation and puts it into application in order to model uncertain activity duration in simulating a real-world system. The purpose of this paper is to assess the usefulness of fuzzy simulation for modeling uncertain activity duration، especially when insufficient or no sample data is available. In this research، fuzzy numbers are used to describe uncertain activity durations which is reflecting vagueness، imprecision and subjectivity in the estimation of them. Initially، a simulation model is designed on the basis of classic (probability distribution-based) approach and then by using activity durations estimated by experts، this model is changed to a fuzzy one. Based on a number of common probability distributions، Some simulation models are designed and their results are compared with those of fuzzy simulation model. The results indicates that، firstly، fuzzy simulation outputs are achieved through only one cycle of fuzzy discrete-event simulation and secondly، the range of fuzzy simulation outputs entails the results of multiple cycles of probability distribution-based simulation experiments. Therefore، the fuzzy simulation is an acceptable approach to present the real system; especially in uncertain circumstances that no sample data is available or there is some insufficient or unreliable data.