Sharif Digital Repository

A new and general procedure for history matching that uses streamline simulation and a gradual deformation technique has been proposed. Streamline trajectories define the major flow paths and help the algorithm to modify the reservoir model only in the regions that cause the mismatch between simulation results and field observations. The use of a gradual deformation technique enables the algorithm to remain constrained to reservoir geostatistics. It also reduces the number of independent variables in the optimization problem. In our algorithm, effective conductivities are defined along each streamline. The effective streamline conductivities are then adjusted using the values of measured and... 

Device-to-Device communication (D2D) integrated in cellular networks emerges as a new trend in response to notable rise in traffic demand. Resource allocation is one of the important challenges in deployment of D2D networks. In this paper, we formulate an optimization problem for optimal resource allocation and then propose a novel algorithm namely maximum clique based resource allocation (MCRA) for improving the spectral reuse based on graph theoretic concept of maximum clique. Practical application of D2D communications requires each node to receive and transmit signals during the communication process. We have considered this issue in constructing the interference graph and mathematical... 

Osmotic power generation is one of the cleaner and sustainable methods for energy generation. This paper presents a study on the optimal size and design of pressure retarded osmosis (PRO) power plant as a viable source of renewable energy in the selected site in Bahmanshir river of Iran. The optimal sizing and design problem is formulated as a Non-Linear Programming (NLP) optimization problem and solved using the standard optimization software titled generalized algebraic modeling system (GAMS). The objective function is minimizing the total cost while considering the technical and economic constraints. Optimization results show that the optimal capacity of the PRO osmotic power plant is... 

The availability of 7-9 GHz of unlicensed spectrum at 60 GHz, advances in low-cost silicon technology, and high interference rejection due to atmospheric loss make 60 GHz an ideal solution for future 4G/5G small-cell backhaul links, where multi-gigabit rates are required. In this article, we review the 60 GHz propagation properties, the practical technology limits, and the regulatory and regional environmental impacts to present a framework for the 60 GHz backhaul link design that translates the link requirements to the essential transmitter and receiver system parameters. This approach includes a preliminary design that generates the input data set for an optimization problem. Two physical... 

To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this... 

In this paper, a novel reinforcement learning method inspired by the way humans learn from others is presented. This method is developed based on cellular learning automata featuring a modular design and cooperation techniques. The modular design brings flexibility, reusability and applicability in a wide range of problems to the method. This paper focuses on analyzing sensitivity of the method's parameters and the applicability in optimization problems. Results of the experiments justify that the new method outperforms similar ones because of employing knowledge sharing technique, reasonable exploration logic, and learning rules based on the action trajectory  

Critical space missions, demand lightweight space structures with high pointing accuracy and dimensional stability in the presence of dynamic and thermal disturbances [1,2]. Therefore both organic-matrix and metal-matrix composites (MMCs) have been developed for space applications [1,2]. Simultaneous reduction of weight and band averaged vibration transmission in a satellite boom structure is the major task of the present study. This study approached the design problem by material selection among a list of MMCs and changing the cross sections of truss members. Optimization problem was solved using GA as a constrained one by new penalty functions  

In this paper, we evaluate the saturation throughput for an IEEE 802.11 based wireless network considering capture effect at the receiver, while nodes transmit with random powers. In this respect, we consider a scenario consisting of a specific number of wireless nodes. Then, we derive the transmission as well as collision probabilities with respect to the perfect capture effect. In order to maximize the saturation throughput we set up an optimization problem and obtain how to compute optimum values for the probabilities corresponding to different power levels. By providing the numerical results, we deduce that power randomization may lead to a significant improvement in saturation... 

Deregulation in power systems has created new uncertainties and increased the previous ones. The presence of these uncertainties causes the transmission network to remain monopoly and the private investors not being interested in investing in this section. This paper presents a new merchant-based transmission expansion planning (TEP) formulation from the viewpoint of private investors. The information-gap decision theory (IGDT) is used to model the inherent uncertainties associated with the estimated investment cost of candidate lines and the forecasted system load and NSGAII is utilized to solve the multi-objective optimization problem. This algorithm helps private investors to select the... 

A novel method to compute guided mode reflectivity from optical waveguide end-facet is presented in this paper. First, rational function fitting method (RFFM) is applied in characteristic Green’s function (CGF) technique to find an approximate closed-form analytic expression for spatial Green’s function of abruptly truncated slab waveguide. Then, derived closed-form relation along with the exact results of spatial Green’s function, obtained by full wave solution, are incorporated in an efficient optimization problem. The fast Newton reflective method with trust region algorithm are utilized for optimized reflection coefficients of guided modes. The main advantage of the proposed CGF-RFFM... 

For a Rayleigh fading full-duplex decode-and-forward relay channel, we analytically derive optimum power allocation schemes subject to individual power constraints for the source and the relay. The optimization problem is taken over the source power and the relay power. It is proven that the optimization problem is concave for this scenario, and optimum power allocations are derived in a closed-form. Finally, the implications of the theoretical results are discussed through the graphs  

The redundancy allocation problem (RAP) is a useful method to enhance system reliability. In most works involving RAP, failure rates of the system components are assumed to follow either exponential or k-Erlang distributions. In real world problems however, many systems have components with increasing failure rates. This indicates that as time passes by, the failure rates of the system components increase in comparison to their initial failure rates. In this paper, the redundancy allocation problem of a series-parallel system with components having an increasing failure rate based on Weibull distribution is investigated. An optimization method via simulation is proposed for modeling and a... 

In this paper, we propose a general delay and stability performance analysis in Heterogeneous Cellular Caching Networks (HCCNs), based on queuing theory. We introduce new performance metrics in HCCNs and propose an optimization problem which minimizes the average experienced delay for users by ensuring the stability of the network. In addition, from the design perspective, we address the problem of finding the minimum cache size for the small cell base stations (SBSs) for having a tolerable average delay and also a stable network. Finally, the analytic expressions derived in this paper are validated through real trace-driven experiments on traffic of YouTube video requests  

An efficient method for computation of surface wave (SW) reflectivity and coupling in an abruptly ended planar layered waveguide is presented. Using characteristic Green's function (CGF) technique, the original structure is approximated by a separable structure. Then by applying rational function fitting method (RFFM) a uniform and closed-form expression of spatial Green's function for separable structure is derived. Having a full wave solution of the original structure, an optimization problem is defined to find the reflection coefficients of SW modes. Unlike the previous presented CGF based method called CGF-complex images (CI), CGF-RFFM leads to easy incorporation of radiation modes... 

This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using... 

The use of advanced cycles to take advantage of the gas turbine's thermodynamic characteristics has received increasing attention in recent years. These cycles have been developed for large scale power generation. Due to the powerful abilities of bio-inspired computing techniques such as Genetic Algorithm in locating the optimal (or near optimal) solutions to a given optimization problem, they are widely utilized for determining the parameters of different engineering systems in order to meet the specified performance objectives for a given problem. In order to illustrate the performance of one of these techniques, development and application of it for an engineering problem is presented. In... 

In this paper, a new genetic algorithm (GA) method is presented to solve the optimization problem in coordination of overcurrent and earth fault relays. In addition to optimal coordination of overcurrent relays, earth fault relays are also coordinated by GA, considering critical fault condition for the relays located in two sides of network's transformers. The objective function is developed by adding new terms that are the constraints related to the coordination of overcurrent and earth fault relays in critical fault conditions considering different winding arrangements of transformers. The paper concluded by the results of a study carried out on a sample power network. The results... 

This paper presents a stochastic framework to properly involve the uncertainties associated with demand in distribution system restoration (DSR) problem. To reach this goal, these uncertainties are represented as probabilistic scenarios corresponding to different load levels. Subsequently, the associated stochastic optimization problem is formulated such that it can be readily solved using dynamic programming approach. Moreover, a clustering technique is presented that enables the dynamic programming approach to find near-optimal solutions for the stochastic load restoration problem with reasonable computational effort. The proposed framework is implemented on a real-world test system, and... 

In a linear accelerator, driven by radio frequency (RF) amplifier stations, one must precisely control the energy gain of the accelerating beam. The RF stations can be viewed as amplifiers placed sequentially to accelerate the beam. This brief presents two control schemes within which the RF stations act as actuators, and a centralized control unit controls the beam energy by acting either on the RF amplitudes or on the RF phases. The control algorithms are based on convex optimization problems with different objectives. The two approaches are successfully tested at the SwissFEL injector test facility using three full-scale RF stations. The two methods are compared from both performance and... 

It is well known that load balancing and low delivery communication cost are two critical issues in mapping requests to servers in Content Delivery Networks (CDNs). However, the trade-off between these two performance metrics has not been yet quantitatively investigated in designing efficient request mapping schemes. In this work, we formalize this trade-off through a stochastic optimization problem. While the solutions to the problem in the extreme cases of minimum communication cost and optimum load balancing can be derived in closed form, finding the general solution is hard to derive. Thus we propose three heuristic mapping schemes and compare the trade-off performance of them through...