Sharif Digital Repository

Nature, as a rich source of solutions, can be an inspirational guide to answer scientific expectations. Seed dispersal mechanism as one of the most common reproduction method among the plants is a unique technique with millions of years of evolutionary history. In this paper, inspired by plants survival, a novel method of optimization is presented, which is called Fertile Field Algorithm. One of the main challenges of stochastic optimization methods is related to the efficiency of the searching process for finding the global optimal solution. Seeding procedure is the most common reproduction method among all the plants. In the proposed method, the searching process is carried out through a... 

A new method for structural optimization is presented for successive approximation of the objective function and constraints in conjunction with Lagrange multipliers approach. The focus is on presenting the methodology with simple examples. The basis of the iterative algorithm is that after each iteration, it brings the approximate location of the estimated minimum closer to the exact location, gradually. In other words, instead of the linear or parabolic term used in Taylor expansion, which works based on a short step length, an arch is used that has a constant curvature but a longer step length. Using this approximation, the equations of optimization involve the Lagrange multipliers as the... 

In this paper, an enriched finite element technique is presented to simulate the mechanism of interaction between the hydraulic fracturing and frictional natural fault in impermeable media. The technique allows modeling the discontinuities independent of the finite element mesh by introducing additional DOFs. The coupled equilibrium and flow continuity equations are solved using a staggered Newton solution strategy, and an algorithm is proposed on the basis of fixed-point iteration concept to impose the flow condition at the hydro-fracture mouth. The cohesive crack model is employed to introduce the nonlinear fracturing process occurring ahead of the hydro-fracture tip. Frictional contact is... 

Hydraulic fracturing (HF) of underground formations has widely been used in different fields of engineering. Despite the technological advances in techniques of in situ HF, the industry uses semi-analytical tools to design HF treatment. This is due to the complex interaction among various mechanisms involved in this process, so that for thorough simulations of HF operations a fully coupled numerical model is required. In this study, using element-free Galerkin (EFG) mesh-less method, a new formulation for numerical modeling of hydraulic fracture propagation in porous media is developed. This numerical approach, which is based on the simultaneous solution of equilibrium and continuity... 

The authors deal with the robust design of multiple-input-multiple-output (MIMO) space-time transmit code (STTC) and space-time receive filter (STRF) for a point-like target embedded in signal-dependent interference. Specifically, they assume that the radar exploits knowledge provided by dynamic environmental database, to roughly predict the actual scattering scenario. Then, they devise an iterative method to optimise the (constrained) STTC and the (constrained) STRF which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm is handled via solving two (hidden) convex optimisation... 

Due to the tight power envelope, in the future technology nodes it is envisaged that not all cores in a many-core chip can be simultaneously powered-on (at full performance level). The power-gated cores are referred to as Dark Silicon. At the same time, growing reliability issues due to process variations and soft errors challenge the cost-effective deployment of future technology nodes. This paper presents a reliability management system for Dark Silicon chips (dsReliM) that optimizes for reliability of on-chip systems while jointly accounting for soft errors, process variations and the thermal design power (TDP) constraint. Towards the TDP-constrained reliability optimization, dsReliM... 

In this paper, we propose an optimized parameter selection procedure for rainbow table Time Memory Trade-Off (TMTO) attack with sequential online search. Unlike previous works that mainly deal with minimizing required memory in the rainbow table TMTO attack we simultaneously focus on the required memory and online search time. Our parameter selection technique is optimized regarding the minimization of the required memory subject to a certain success probability and a maximum online search time. Obtained results are two compact mathematical expressions for determining rainbow table TMTO attack parameters, number and length of chains. The application of our optimized parameter selection... 

In this paper, we develop and analyze a novel performance metric, called interference efficiency (IE), that shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the IE of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power on PU receiver, total SUs transmit power and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP), that aims to achieve the maximum ergodic sum rate of multiple SUs and the minimum average interference power on the... 

In this paper, we develop and analyze a novel performance metric, called interference efficiency, which shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the interference efficiency of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power, total transmit power, and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP) that aims to maximize ergodic sum rate of SUs and to minimize average interference power on the primary receiver. We solve... 

This letter is concerned with designing incoherent unit-norm frames, i.e., a set of vectors in a finite dimensional Hilbert space with unit norms and very low absolute pairwise correlations. Due to their widespread use in a variety of applications, including compressed sensing and coding theory, incoherent frame design has received considerable attention, and many algorithms have been proposed to this aim. In this letter, a new algorithm is presented which constructs incoherent frames by minimizing the maximum absolute pairwise correlations (mutual coherence) of the frame vectors. Our strategy is based on an alternating minimization penalty method, which admits efficient solvers using... 

This paper is concerned with designing efficient algorithms for recovering sparse signals from noisy underdetermined measurements. More precisely, we consider minimization of a nonsmooth and nonconvex sparsity promoting function subject to an error constraint. To solve this problem, we use an alternating minimization penalty method, which ends up with an iterative proximal-projection approach. Furthermore, inspired by accelerated gradient schemes for solving convex problems, we equip the obtained algorithm with a so-called extrapolation step to boost its performance. Additionally, we prove its convergence to a critical point. Our extensive simulations on synthetic as well as real data verify... 

This paper proposes a constrained stochastic successive convex approximation (CSSCA) algorithm to find a stationary point for a general non-convex stochastic optimization problem, whose objective and constraint functions are non-convex and involve expectations over random states. Most existing methods for non-convex stochastic optimization, such as the stochastic (average) gradient and stochastic majorization-minimization, only consider minimizing a stochastic non-convex objective over a deterministic convex set. The proposed CSSCA algorithm can also handle stochastic non-convex constraints in optimization problems, and it opens the way to solving more challenging optimization problems that... 

By exponential increase in applications of the Internet of Things (IoT), such as smart ecosystems or e-health, more security threats have been introduced. In order to resist known attacks for IoT networks, multiple security protocols must be established among nodes. Thus, IoT devices are required to execute various cryptographic operations, such as public key encryption/decryption. However, classic public key cryptosystems, such as Rivest-Shammir-Adlemon and elliptic curve cryptography are computationally more complex to be efficiently implemented on IoT devices and are vulnerable regarding quantum attacks. Therefore, after complete development of quantum computing, these cryptosystems will... 

Secure and reliable operation is one of the main challenges in restructured power systems. Wind energy has been gaining increasing global attention as a clean and economic energy source, despite the operational challenges its intermittency brings. In this study, we present a formulation for electricity and reserve market clearance in the presence of wind farms. Uncertainties associated with generation and line outages are modeled as different system scenarios. The formulation incorporates the cost of different scenarios in a two-stage short-term (24-hours) clearing process, also considering different types of reserve. The model is then linearized in order to be compatible with standard... 

In this paper, we show how time-sharing method may reduce transmission delay in the dynamic index coding scenario. We propose a novel time-shared dynamic index coding transmission scheme that achieves the maximum index coding gain for a complete bi-directional side information graph and formulate a constrained optimization problem to tune the transmission scheme for the minimum transmission delay. A closed-form solution is presented for the special case of two-user. We also use analytical and simulation results to provide graphical intuition for the obtained results  

Continuity of supply plays a significant role in modern distribution system planning and operational studies. Accordingly, various techniques have been developed for reliability assessment of distribution networks. However, owing to the complexities and restrictions of these methods, many researchers have resorted to several heuristic optimization algorithms for solving reliability-constrained optimization problems. Therefore, solution quality and convergence to global optimality cannot be guaranteed. Aiming to address this issue, two salient mathematical models are introduced in this paper for topology-variable-based reliability evaluation of both radial and radially-operated meshed... 

This article addresses a centralized generation expansion planning problem, accounting for both long- and short-term uncertainties. The long-term uncertainty (demand growth) is modeled via a set of scenarios, while the short-term uncertainty (wind power generation) is described by a family of probability distributions with the same first- and second-order moments obtained from historical data. The resulting model is a distributionally robust chance-constrained optimization problem, which selects the conventional generating units to be built among predefined discrete options. This model includes a detailed representation of unit commitment constraints. To achieve computational tractability,... 

In this paper, a cross-layer approach introducing new design parameters is developed for multi-rate wireless links. The novel design jointly exploits the finite-length queuing at the data link layer and the adaptation capability of the adaptive modulation and coding (AMC) scheme at the physical layer to optimize system performance for a wireless link. The analytical framework is based on discrete time Markov Chain. The performance metrics such as packet drop probability, channel packet error rate and packet loss rate are derived. Using these metrics, a constrained optimization problem is solved numerically to maximize the overall system throughput  

Short term hydrothermal scheduling (STHTS) is a non-linear, multi-modal and very complex constrained optimization problem which has been solved using several conventional and modern metaheuristic optimization algorithms. A number of research articles have been published addressing STHTS using different techniques. This article presents a comprehensive review of research published for solving the STHTS problem in the last four decades. © 2013 IEEE  

For several years, a substantial effort has been devoted to the study of 3-D source localization based on 2-D arrays by measuring the well-known azimuth and elevation angles. However, studies on 3-D source localization performed by 1-D arrays are still lacking. Perhaps, the most important drawback in the deployment of a 2-D array structure lies in the fact that it needs a planar space, which might not be available in some applications. This letter concentrates on the problem of 3-D source localization based on 1-D angle measurement provided by a linear array. Different from the traditional 2-D structures where each measurement induces a straight line, each measurement in the 1-D array...