Sharif Digital Repository

Urban rail planning is extremely complex, mainly because it is a decision problem under different uncertainties. In practice, travel demand is generally uncertain, and therefore, the timetabling decisions must be based on accurate estimation. This research addresses the optimization of train timetable at public transit terminals of an urban rail in a stochastic setting. To cope with stochastic fluctuation of arrival rates, a two-stage stochastic programming model is developed. The objective is to construct a daily train schedule that minimizes the expected waiting time of passengers. Due to the high computational cost of evaluating the expected value objective, the sample average... 

An adaptive approach for distribution system reconfiguration and charging management of plug-in electric vehicles (PEV) is presented in this study. A stochastic model predictive control is applied to stochastically, adaptively, and dynamically reconfigure the system, manage the incidental charging pattern of PEVs, and deal with the variable and uncertain power of renewable energy sources. The objective function of problem is minimizing daily operation cost of system. Herein, the geography of area is considered and the behavior of PEVs' drivers (based on their income level) is modeled with respect to the value of incentive and their hourly distance from each charging station. It is shown that... 

Infrastructure as a Service (IaaS) is one of the most significant and fastest growing fields in cloud computing. To efficiently use the resources of an IaaS cloud, several important factors such as performance, availability, and power consumption need to be considered and evaluated carefully. Evaluation of these metrics is essential for cost-benefit prediction and quantification of different strategies which can be applied to cloud management. In this paper, analytical models based on Stochastic Reward Nets (SRNs) are proposed to model and evaluate an IaaS cloud system at different levels. To achieve this, an SRN is initially presented to model a group of physical machines which are... 

In this paper, Stochastic Activity Networks (SANs) are exploited to model and evaluate the power consumption and performance of virtualized servers in cloud computing. The proposed SAN models the physical servers in three different power consumption and provisioning delay modes, switching the status of the servers according to the workload of the corresponding cluster if required. The Dynamic Voltage and Frequency Scaling (DVFS) technique is considered in the proposed model for dynamically controlling the supply voltage and clock frequency of CPUs. Thus, Virtual Machines (VMs) on top a physical server can be divided into several power consumption and processing speed groups. According to the... 

This paper deals with energy management of microgrids during unscheduled islanding events, initiated by disturbances in the main grid. In these situations, the main challenge is uncertainty about duration of disconnection from the main grid. In order to tackle this issue, a stochastic framework is proposed for optimal scheduling of microgrid resources over this period. The presented framework addresses the prevailing uncertainties of islanding duration as well as prediction errors of demand and renewable power generation. According to this framework, the probability distribution of islanding duration needs to be estimated, instead of predicting its exact value. The objective is to minimize... 

The railroad blocking problem is classified in the tactical level of freight rail transportation problems. The objective of this problem is to determine the optimal paths for each shipment such that the railway limitations are satisfied. In this problem, the quantities of both demand and supply resource indicators are often assumed to be certain and known, but because a blocking solution is designed for a relatively long period of time, this assumption is not reasonable. In this paper, we have developed a two-stage stochastic program for this problem to consider the uncertainty inherent in demand and supply resource indicators. Due to the size and complexity of the stochastic program and the... 

This paper presents a mathematical model using Stochastic Activity Networks (SANs) to model a grid resource, and compute the throughput of a resource in servicing grid tasks, wherein the failure–repair behavior of the processors inside the resource is taken into account. The proposed SAN models the structural behavior of a grid resource and evaluates the combined performance and availability measure of the resource. Afterwards, the curve fitting technique is used to find a suitable function fitted to the throughput of a resource for grid tasks. Having this function and the size of each grid job based on its tasks, an algorithm is proposed to compute the makespan of each available resource to... 

Outpatient appointment scheduling problems have recently gained increasing attention. This paper provides a comprehensive review of recent analytical and numerical optimization studies that present decision-support tools for designing and planning outpatient appointment systems (OASs). A structure for organizing the recent literature according to various criteria is provided, including a framework that classifies decisions at the strategic, tactical, and operational levels. The OAS literature is evaluated from four perspectives: problem settings, environmental factors, modeling approaches, and solution methods. In addition, research gaps and areas of opportunity for future research are... 

Proliferation of distributed generations (DGs) and power-electronics-based loads is bringing about more harmonic-polluted power signals. While some failures may occur as a consequence of nonsinusoidal current or voltage waveforms, existing reliability models of protection relays have not taken the harmonic-related failures into consideration. This paper develops a comprehensive Markov reliability model to categorize the possible functional states of a component, say a transmission line, protected by a relay, operating in a harmonic-polluted environment. In order to make the proposed model practically tractable, it is further simplified in two ways, through merging the states of the same... 

This article introduces a new time-varying model to generate synthetic non-stationary acceleration records using the modified Kanaii-Tajimi model with time-variant parameters. The proposed method can capture two different dominant frequencies per time which makes it suitable for synthesizing the near-field no-pulse earthquake records. A number of closed-form relationships are developed to describe the frequency dependent time-domain level crossings of the simulated records under white noise excitation. The model parameters are optimized using the crossing and Arias intensity properties of the synthetic and target records. The efficiency of the proposed model is demonstrated using a data base... 

This paper presents a stochastic framework for day-ahead scheduling of microgrid energy storage systems in the context of multi-objective (MO) optimization. Operation cost of microgrid in normal conditions and load curtailment index in case of unscheduled islanding events (initiated by disturbances in the main grid) are chosen as main criteria of the proposed scheme. In practice, duration of disconnection from the upstream network is unknown in unscheduled islanding incidents and cannot be predicted with certainty. To properly handle the uncertainties associated with time and duration of such events as well as microgrid load and renewable power generation, stochastic models are involved in... 

This paper investigates the role of parking lots in improving the reliability of renewable-based distribution systems, through provision of vehicle-to-grid (V2G) programs during outage events. In this regard, municipal parking decks are viewed as distributed energy storage systems and the amount of available energy from these units in random contingency events is probabilistically modeled for reliability studies. Appropriate stochastic models are also introduced to capture the volatility and intermittency of renewable sources. Moreover, it is discussed that how the adopted outage management scheme (OMS) in contingency events can affect the reliability level of customers. In response, several... 

This paper develops a stochastic multi-period mixed-integer model for collection, production, storage, and distribution of platelet in Blood Transfusion Organizations ranging from blood collection centers to clinical points. In this model, the age of platelet and ABO-Rh priority matching rules are incorporated based on the type of patient to raise the quality and safety of platelet transfusion services. At first, a discrete Markov Chain Process is applied to predict the number of donors. Afterwards, the uncertain demand is captured using a two-stage stochastic programming. A challenging aspect of applying stochastic programming in a dynamic setting is to construct an appropriate set of... 

Integrating independent dispatchable and non-dispatchable resources into a micro-grid platform enables the main power systems to benefit from the economic and environmental advantages of distributed generation while facilitating local, clean, and inexhaustible renewable energy production. Moreover, it makes the integrated components more visible and controllable for the whole power system. On the other hand, to properly handle multiple uncertainties inherent in the micro-grids, probabilistic energy management techniques are deployed. However, utilization of stochastic modeling and optimization tools for efficient, reliable, and cost-effective planning, operation, and control of micro-grids... 

Long and continuous running of software can cause software aging-induced errors and failures. Cloud data centers suffer from these kinds of failures when Virtual Machine Monitors (VMMs), which control the execution of Virtual Machines (VMs), age. Software rejuvenation is a proactive fault management technique that can prevent the occurrence of future failures by terminating VMMs, cleaning up their internal states, and restarting them. However, the appropriate time and type of VMM rejuvenation can affect performance, availability, and power consumption of a system. In this paper, an analytical model is proposed based on Stochastic Activity Networks for performance evaluation of... 

In this paper, Stochastic Activity Networks (SANs) are used to model and evaluate the performance and power consumption of an Infrastructure-as-a-Service (IaaS) cloud. The proposed SAN model is scalable and flexible, yet encompasses some details of an IaaS cloud, such as Virtual Machine (VM) provisioning, VM multiplexing, and failure/repair behavior of VMs. Using the proposed SAN, a power-aware self-adaptive resource management scheme is presented for IaaS clouds that automatically adjusts the number of powered-on Physical Machines (PMs) regarding variable workloads in different time intervals. The proposed scheme respects user-oriented metrics by avoiding Service Level Agreement (SLA)... 

The great share of interruptions in distribution networks motivates distribution decision makers to establish various reliability enhancement strategies. Amongst, deploying remote controlled switch (RCS) can make a crucial contribution to the reduction of interruption costs. Nevertheless, the stochastic nature of contingencies affects the RCS worth and imposes substantial financial risk to RCS deployment projects. This paper proposes a mathematical model to consider the risk in the optimal RCS deployment problem. The model determines the number and location of RCSs such that the expected profit is maximized while financial risk is minimized. The risk is modeled through conditional... 

Energy Harvesting (EH) is a novel technique to prolong the lifetime of the wireless Ad-hoc and sensor networks with replenishable nodes. In this sense, it has emerged as a promising technique for Green Communications. On the other hand, cooperative communication with the help of relay nodes improves the performance of wireless communication networks. In this paper, we investigate the cooperation in EH nodes. We consider the optimal power and rate allocation in the full-duplex Gaussian relay channel in which source and relay can harvest energy from their environments. In our model, the energy arrivals at the source and the relay are general stochastic processes with known EH times and amounts... 

This paper introduces an efficient stochastic method to produce fully nonstationary records having multiple peaks in power spectrum. The zero-crossing characteristics of the acceleration, velocity, and displacement time histories of the output signal are used to estimate the model parameters. This procedure is utilized to resimulate 252 non-pulse-like, horizontal near-field records with rupture distance of less than 10 km and strike–slip mechanism. The model parameters are regressed against moment magnitude, rupture distance, hypo-central depth, and shear wave velocity, enabling the scenario-based simulation of the records. The response spectra of the simulated records are compared with... 

Besides increasing the installation of distributed generation plants, investigation on multi-carrier energy systems leads recent studies to focus on several aspects of Smart Energy Hub (S. E. Hub) systems. An S. E. Hub incorporates several modules which calculation of optimal size and operation of each have already attracted a great deal of research. Uncertainty in the modeling of these modules is an imperative factor that was not paid attention in S. E. Hub models properly. To build up a more precise framework for S. E. Hubs, here we present a stochastic model for real time electricity and natural-gas prices and electricity demands. In this paper, an S. E. Hub operates in order to minimize...