Sharif Digital Repository

We have entered the era of networked communications where concepts such as big data and social networks are emerging. The explosion and profusion of available data in a broad range of application domains cause data streams to become an inevitable part of the most real-world applications. In the classification of data streams, there are four major challenges: infinite length, concept drift, recurring and evolving concepts. This paper proposes a novel method to address the mentioned challenges with a focus on the last one. Unlike the existing methods for detection of evolving concepts, we cast joint classification and detection of evolving concepts into optimizing an objective function by... 

We have entered the era of networked communications where concepts such as big data and social networks are emerging. The explosion and profusion of available data in a broad range of application domains cause data streams to become an inevitable part of the most real-world applications. In the classification of data streams, there are four major challenges: infinite length, concept drift, recurring and evolving concepts. This paper proposes a novel method to address the mentioned challenges with a focus on the last one. Unlike the existing methods for detection of evolving concepts, we cast joint classification and detection of evolving concepts into optimizing an objective function by... 

A resource investment problem with discounted cash flows is a project scheduling problem in which the availability levels of the resources are considered decision variables and the goal is to find a schedule and resource requirement levels such that the net present value of the project cash flows optimizes. In this paper, we present a genetic algorithm to solve this problem. We explain the elements of the algorithm such as chromosome structure, fitness function, crossover, mutation, and local improvement operations and solve more than 220 problems with known optimal solutions to evaluate the performance of the proposed algorithm. The results of the experimentation are quite satisfactory. ©... 

This paper presents a new method to determine the optimal number and locations of autorecloser and sectionalizer switches (AR/S) in distribution networks. The costs of AR/S investment, switch maintenance, and undistributed energy as well as reliability coefficients are considered in the objective function. Reliability parameters such as SAIFI, SADI, MAIFI, and ENS are evaluated in the case study system. As a new method, the weights of the reliability parameters are obtained by decision-makers using the analytical hierarchy process (AHP). The optimal size, type, and location of automatic switches are determined by minimizing the objective function using the particle swarm optimization (PSO)... 

In this paper, an adaptive random search method, based on continuous action-set learning automata, is studied for solving stochastic optimization problems in which only the noisecorrupted value of a function at any chosen point in the parameter space is available. First, a new continuous action-set learning automaton is introduced and its convergence properties are studied. Then, applications of this new continuous action-set learning automata to the minimization of a penalized Shubert function and pattern classification are presented. © Sharif University of Technology  

Recently, many investigations have been studied on the effects of the uncommon extreme events like hurricanes in electrical distribution grids. These events leads to damage to distribution grid equipments, and they are cause widespread blackouts. This paper presents short-term resilience enhancement of the residential sections against hurricane at day-ahead. The lines outage in the electrical distribution grid is implemented as stochastic modeling by hurricane. The resilience enhancement is done in the multiple energy systems such as integrated gas, heat and electrical. The three-stage multi-objective functions optimization is proposed for resilience-oriented enhancement. The proposed... 

This study proposes an imperialist competition algorithm (ICA) to maximise the benefits of distribution network operators (DNOs) because of the existence of distributed generation (DG) units. The sum of active loss reduction and network investment deferral incentives has been considered as the objective function to be maximised in this study. The optimal location and size of DG units in the network are found considering various techno-economical issues. The application of the proposed methodology in the UK under current Ofgem financial incentives for DNOs is investigated. The ability of the proposed approach in finding the optimal solution is validated by comparing the obtained results with... 

Multi-floor facility layout problem concerns the arrangement of departments on the different floors. In this paper, a new mathematical model is proposed for multi-floor layout with unequal department area. Maximising the number of useful adjacencies among departments is considered as the objective function. The adjacencies are divided into two major categories: horizontal and vertical adjacencies. The horizontal adjacency may be occurred between the departments assigned to same floors while the vertical can be happened between departments assigned to any consecutive floors. A minimum common boundary length (surface area) between any two horizontal (vertical) adjacent departments is... 

We study the problem of causal structure learning when the experimenter is limited to perform at most k non-adaptive experiments of size 1. We formulate the problem of finding the best intervention target set as an optimization problem, which aims to maximize the average number of edges whose directions are resolved. We prove that the corresponding objective function is submodular and a greedy algorithm suffices to achieve (1 - approximation of the optimal value. We further present an accelerated variant of the greedy algorithm, which can lead to orders of magnitude performance speedup. We validate our proposed approach on synthetic and real graphs. The results show that compared to the... 

In this study, the cost function of the defined system is derived first. Then, we prove this function is convex in the system's base stock level. Finally, based on the convexity of the cost function, the optimal solution for the base stock model is determined. For demonstrating the applicability of the proposed method, we resort to solving an example. © 2009 Asian Network for Scientific Information  

This paper proposes a solution for multiple-impulse orbital maneuvers near circular orbits for special cases where orbital observations are not globally available and the spacecraft is being observed through a limited window from a ground or a space-based station. The current study is particularly useful for small private launching companies with limited access to global observations around the Earth and for orbital maneuvers around other planets for which the orbital observations are limited to the in situ equipment. An appropriate cost function is introduced for the sake of minimizing the total control/impulse effort as well as the orbital uncertainty. It is subsequently proved that for a... 

This paper proposes a novel method to design an H∞-optimal Fractional Order PLD (FOPLD) controller with ability to control the transient, steady-state response and stability margins characteristics. The method uses particle swarm optimization algorithm and operates based on minimizing a general cost function. Minimization of the cost function is carried out subject to the H∞-norm; this norm is also included in the cost function to achieve its lower value. The method is applied to a phase-locked-loop motor speed system and an electromagnetic suspension system as two examples to illustrate the design procedure and verify performance of the proposed controller. The results show that the... 

Presented within this paper is the identification of impact force acting on a simply supported beam. The force identification is an inverse problem in which the measured response of the structure is used to determine the applied force. The identification problem is formulated as an optimization problem and genetic algorithm is utilized to solve the optimization problem. The objective function is calculated on the difference between analytical and measured responses and the decision variables are the location and magnitude of the applied force. The results from simulation show the effectiveness of the approach and its robustness to the measurement noise and sensor location  

Primal-Dual Interior-Point Methods (IPMs) have shown their power in solving large classes of optimization problems. In this paper a self-regular proximity based Infeasible Interior Point Method (IIPM) is proposed for linear optimization problems. First we mention some interesting properties of a specific self-regular proximity function, studied recently by Peng and Terlaky, and use it to define infeasible neighborhoods. These simple but interesting properties of the proximity function indicate that, when the current iterate is in a large neighborhood of the central path, large-update IIPMs emerge as the only natural choice. Then, we apply these results to design a specific self-regularity... 

In this research, the handling behavior of an intermediate class passenger car has been optimized by altering its front suspension parameters. For this purpose, a validated virtual model of the car, constructed by Adams/Car software, has been used. The utilized objective function is a combination of eight criteria indicating handling characteristics of the car. To reduce the amount of optimization parameters, a sensitivity analysis has been done by implementing the Design of Experiments method capabilities. Optimization has been done using the Response Surface Method. The obtained optimization results show a considerable improvement in the system response. Copyright © 2006 SAE International  

This paper approaches the topic of protection system reliability from an economic point of view by 1) designing an optimal modern protective relay based on a prescribed level of reliability subject to economic constraints and 2) determining optimal routine test intervals by balancing the cost of routine tests and losses due to relay failure. This paper proposes a method that enables the designer to optimally select hardware and software components of a digital protective relay to gain the highest possible overall reliability with a restricted budget. This design can be viewed as a reliability and redundancy allocation problem for which a new easy-to-implement algorithm is proposed. In... 

In this paper, we present a novel approach to generate images of extended depth-of-field (DOF) to support realization of three-dimensional (3D) imaging systems such as integral imaging. In our approach in extending the DOF, we take advantage of the spatial frequency spectrum of the object specific to the task in hand. The pupil function is thus engineered in such a fashion that the modulation transfer function (MTF) is maximized only in these selected spatial frequencies. We extract these high energy spatial frequencies using the principal component analysis (PCA) method. Moreover, given the need for many pupil function engineering steps in 3D imaging systems, we have constructed an... 

In this paper, a class of uncertain piecewise affine (PWA) systems, subject to system and measurement external disturbances are studied. The uncertainties are assumed to be norm bounded and the external disturbance signals belong to the L2 space. The problem of optimizing the system response in the H?sense, by means of a piecewise affine observer-controller, is formulated as an optimization problem subject to a number of constraints in the form of matrix inequalities. The derived constraints are obtained by considering a partially piecewise quadratic Lyapunov function in combination with the general conditions for H?stability. Then the uncertain PWA approximation of the nonlinear attitude... 

A novel and robust approach is proposed to find the optimum shape of concrete arch dams located on any unsymmetrical shape of a valley. The approach is capable of finding the optimum shape for any given valley type in suitable time, based on abutment stability analysis, against thrust forces from an arch dam. The behavior and stability of a concrete arch dam is strongly dependent on the bedrock on which the dam rests. The stability of the abutment is considered a constraint in the proposed approach. In addition, a new objective function is introduced to decrease the final volume of the arch dam. Furthermore, a computer program was developed, which takes the effect of the dam foundation...