Sharif Digital Repository

The usage of conventional fossil fuels has aided fast economic growth while also having negative consequences, such as increased global warming and the destruction of the ecosystem. This paper proposes a novel swarm-based metaheuristic method called Chimp Optimization Algorithm (ChOA) to tackle the environmental, economic dispatch issue and reducing the waste nonrenewable materials. In this regard, two objective functions named fuel cost function and emission cost function are proposed. Unique constrained handling also solves the challenge of multi-objective optimization. Standard IEEE 30 bus with six generators and a 10-unit system are used to demonstrate the usefulness of ChOA. The result... 

This letter proposes a dictionary learning algorithm for blind one bit compressed sensing. In the blind one bit compressed sensing framework, the original signal to be reconstructed from one bit linear random measurements is sparse in an unknown domain. In this context, the multiplication of measurement matrix A and sparse domain matrix φ, i.e., D = Aφ, should be learned. Hence, we use dictionary learning to train this matrix. Towards that end, an appropriate continuous convex cost function is suggested for one bit compressed sensing and a simple steepest-descent method is exploited to learn the rows of the matrix D. Experimental results show the effectiveness of the proposed algorithm... 

This letter proposes a sparse diffusion algorithm for 1-bit compressed sensing (CS) in wireless sensor networks, and the algorithm is inherently robust against impulsive noise. The approach exploits the diffusion strategy from distributed learning in the 1-bit CS framework. To estimate a common sparse vector cooperatively from only the sign of measurements, a steepest descent method that minimizes the suitable global and local convex cost functions is used. A diffusion strategy is suggested for distributive learning of the sparse vector. A new application of the proposed algorithm to sparse channel estimation is also introduced. The proposed sparse diffusion algorithm is compared with both... 

In this paper, a combined model of auto-transit assignment is introduced based on two complementarity formulations in the literature. The model accounts for interactions between the auto and transit modes through non-separable asymmetric demand and cost functions. A path-based solution algorithm is presented based on the three ideas of decomposition, column generation, and linearization, which have proved to be effective in tackling large-size networks. Numerical results over the Chicago sketch network suggest that the algorithm converges quickly within the first iterations, but is less effective as the solution gets closer to the neighborhood of the equilibrium solution. The sluggish... 

In this paper, we propose two methods for signal denoising where both signal and noise are sparse but in different domains. First, an optimization problem is proposed which is non-convex and NP-hard due to the existence of ℓ 0 norm in its cost function. Then, we propose two approaches to approximate and solve it. We also provide the proof of convergence for the proposed methods. The problem addressed in this paper arises in some applications for example in image denoising where the noise is sparse, signal reconstruction in the case of random sampling where the random mask is unknown, and error detection and error correction in the case of missing samples. The experimental results indicate... 

This paper will first describe the Linear Quadratic Regulator (LQR) and Fuzzy logic controller when the Proportional-Integral-Derivative (PID) controllers are inactive for procedures that have large delay time (LDT) in transfer stage. Therefore in those states, LQR and Fuzzy controllers perform better than the PID controllers. The constrained LQR is optimal and stabilizing. The solution algorithm is guaranteed to terminate in finite time with a computational cost that has a reasonable upper bound compared to the minimal cost for computing the optimal solution. The system determines the amount of fuel required from a fuzzy algorithm to arrive at the desired temperature. The parameters of the... 

This paper proposes a novel method to designing an H∞ PID controller with robust stability and disturbance attenuation. This method uses particle swarm optimization algorithm to minimize a cost function subject to-norm to design robust performance PID controller. We propose two cost functions to design of a multiple-input, multiple-output (MIMO) and single-input, single-output (SISO) robust performance PID controller. We apply this method to a SISO flexible-link manipulator and a MIMO super maneuverable F18/HARV fighter aircraft system as two challenging examples to illustrate the design procedure and to verify performance of the proposed PID controller design methodology. It is shown with... 

This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in direction of arrival (DOA) estimation from both the array sensor data and from the sign of the array sensor data. Discretization of the grid in the sparsity-based DOA estimation algorithms is a problem, which leads to a bias error. To compensate this bias error, a dictionary learning technique is suggested, which is based on minimizing a suitable cost function. We also propose an algorithm for the estimation of DOA from the sign of the measurements. It extends the iterative method with adaptive thresholding algorithm to the 1-b compressed sensing framework. Simulation results show the effectiveness... 

This communication addresses the focusing problem in the millimeter-wave imaging systems. We categorize the focusing problem into the frequency focusing for wideband systems and the range focusing for narrowband systems. In an out-of-focus wideband system, a shifted shadow of the object is present in the reconstruction, whereas for a range out of the focused system, the recovered images are blurred. To overcome these issues, first, we theoretically show that the defocusing variations for both categories are bounded. Then, we present a universal formulation for focusing problem, which covers both wideband and narrowband systems. As the true focused images are sharp at the boundaries of the... 

This study is dedicated to order penetration point (OPP) strategic decision making which is the boundary between make-to-order (MTO) and make-to-stock (MTS) policies. A multiproduct multiechelon production supply chain is considered where the first production stage manufactures semifinished products based on an MTS policy to supply the second production stage which operates on the MTO policy. The producer desires to find the optimal fraction of processing time fulfilled by supplier and optimal semifinished products buffer capacity in OPP. To calculate system performance indexes, the matrix geometric method is employed. Afterward, optimal solutions are obtained by enumeration and direct... 

In this paper, we propose a new optimization technique by modifying a chaos optimization algorithm (COA) based on the fractal theory. We first implement the weighted gradient direction-based chaos optimization in which the chaotic property is used to determine the initial choice of the optimization parameters both in the starting step and in the mutations applied when a convergence to local minima occurred. The algorithm is then improved by introducing a method to determine the optimal step size. This method is based on the fact that the sensitive dependence on the initial condition of a root finding technique (such as the Newton-Raphson search technique) has a fractal nature. From all roots... 

In this paper, a multiproduct single-machine production system under economic production quantity (EPQ) model is studied in which the existence of only one machine causes a limited production capacity for the common cycle length of all products, the production defective rates are random variables, shortages are allowed and take a combination of backorder and lost sale, and there is a service rate constraint for the company. The aim of this research is to determine the optimal production quantity, the allowable shortage level, and the period length of each product such that the expected total cost, including holding, shortage, production, setup and defective items costs, is minimized. The... 

In this paper, an Economic Production Quantity (EPQ) model is studied, in which the production defective-rate follows either a uniform or a normal probability distribution. Shortages are allowed and take a backorder state, and the existence of only one machine causes a limited production capacity for the common cycle length of all products. The aim of this research is to determine the optimal production quantity of each product, such that the expected total cost including holding, shortage, production, setup and defective items cost is minimized. The mathematical model of the problem is derived, for which the objective function is proved to be convex. Then, a derivative approach is utilized... 

The main objective of this research was to introduce a smart assist-as-needed control system that helps elderly or partially paralyzed individuals. To ensure that a smart and compliant controller, in each cycle of the gait is developed, we adapted the target impedance gains and feed-forward force of the assistive mechanism according to a learning law. A strength metric was defined to determine when the human needs assistance. Then, a cost function was introduced and the gains are modified to reduce the cost function. Applying the proposed controller, the interaction force between patient's limb and robot was reduced in cases wherein user has sufficient strength for task execution and...