Sharif Digital Repository

In this paper, the optimal performance of a planar humanlike musculoskeletal arm is investigated during reaching movements employing an optimal control policy. The initial and final states (position and velocity) are the only known data of the response trajectory. Two biomechanical objective functions are taken into account to be minimized as the central nervous system (CNS) strategy: (1) a quadratic function of muscle stresses (or forces), (2) total time of movement plus a quadratic function of muscle stresses. A two-degress of freedom (DOF) nonlinear musculoskeletal arm model (for planar movements) with six muscle actuators and four state variables is used in order to evaluate the proposed... 

The optimal design of a casting feeding system is considered. The riser topology is systematically modified to minimize the riser volume, while simultaneously ensuring that no defect appears in the product. In this approach, we combine finite-difference analysis of the solidification process with evolutionary topology optimization to systematically improve the feeding system design. The outstanding features of the presented method are: its efficiency, ease of implementation and simplifying definition of the initial design. The efficiency and capability of the presented method are supported by illustrative examples. © 2008 Springer-Verlag  

This paper presents an electric arc furnace (EAF) optimization framework intended to define optimal control profiles for the EAF, in order to increase its efficiency and thus reduce the energy consumption. The framework aims to minimize controllable losses and to maximize energy transfer to the bath and, consequently, minimize the operational costs. This is achieved through improved actuation of the EAF inputs, i.e., transformer power, oxygen lancing, and carbon addition. To achieve maximal energy transfer to the bath and to reduce the heat losses from the arcs, proper properties of the slag, such as foaminess and basicity, are a subject of considerable attention. The framework is designed... 

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... 

The desired milling process with high material removal rate (MRR) and low surface roughness of the product can be achieved only if machining chatter is absent. Incorporating chatter into the optimal selection of the machining parameters leads to a complex problem. Therefore, the approach of selecting conservative intervals for the machining parameters is usually employed instead. In this paper, a practical approach is proposed to specify the optimal machining parameters (depth of cut and spindle speed) in order to maximize MRR and minimize forced vibrations by considering machining chatter. Firstly, the worst-case scenario-based optimization problem in terms of the surface quality is solved... 

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

The huge availability of data in the last decade has raised the opportunity for the better use of data in decision-making processes. The idea of using the existing data to achieve a more coherent reality solution has led to a branch of optimization called data-driven optimization. On the one hand, the presence of uncertain variables in these datasets makes it crucial to design robust optimization methods in this area. On the other hand, in many real-world problems, the closed-form of the objective function is not available and a meta-model based framework is necessary. Motivated by the above points, in this paper a Gaussian process is used in a Bayesian optimization framework to design a... 

The surface plasmon effect of Au nanostructures placed on the surface of hematite has recently been used to enhance light absorption within its carrier collection distance of 10 nm from the water-hematite interface. Despite significant narrow band absorption enhancements in the visible region, the reported enhancements in the overall performance of the cell under standard AM1.5 sunlight illumination are not significant. We numerically design an array of Au stripes on the surface of an extremely thin layer of hematite to maximize the number of charge carriers that can reach the hematite-water interface and explore the optical processes involved. The lateral dimensions and in particular the... 

Microburst wind shear is a potential hazard for aviation safety, especially in some crucial phases of flight like take-off and landing. Optimal trajectories could be useful for suitable retrieval of transport aircrafts encountering microburst. These types of trajectories are investigated in this paper for landing phase in two scenarios of escape and landing utilizing the most recent realistic analytical model of the microburst. In this regard, a set of complete six degrees of freedom aircraft's equations of motion is taken in a variation formulation of this problem. This approach is particularly useful for determination of optimal escape or approach trajectories constrained with respect to... 

Nowadays, many manufacturing and service systems provide products and services to their customers in several consecutive stages of operations, in each of which one or more quality characteristics of interest are monitored. In these environments, the final quality in the last stage not only depends on the quality of the task performed in that stage but also is dependent on the quality of the products and services in intermediate stages as well as the design parameters in each stage. In this paper, a novel methodology based on the posterior preference approach is proposed to robustly optimize these multistage processes. In this methodology, a multi-response surface optimization problem is... 

Once the path of the vehicle and the desired task of the end-effector are predefined, in order to apply the optimal stability criterion, the manipulator should be redundant. In this paper, the goal is to find the position, angular velocity, and angular acceleration of the redundant link of the manipulator such that the entire system becomes optimally stable. By considering the full dynamic interaction between the manipulator and its vehicle, the stability issue becomes more complex. There are some measures of stability and one of them is the tire's upward force. This measure tries to equalize the upward forces of the tires that lead to optimal stability and better steer-ability. Optimizing... 

In this work, the wind farm layout optimization problem is dealt with using a new approach. The aim of wind farm layout optimization is to maximize the output power of a wind farm considering the wake losses. Layout optimization minimizes the wake losses regarding the location of the turbines. Three different wind scenarios with different wind direction angles, wind direction blowing probabilities, and Weibull distribution parameters are assumed. Since, the problem is nonlinear and constrained, imperialist competitive algorithm is used as a modern and powerful algorithm for continuous optimization problems. The optimization outcomes indicate that imperialist competitive algorithm yields... 

The present paper deals with the design and optimization of a heat driven thermoacoustic refrigerator. A simplified model is developed which enables to pinpoint and examine the most important physical characteristics of a compact traveling wave thermoacoustic refrigerator driven by a traveling wave thermoacoustic engine. The model can explain the so-called traveling standing wave effect in thermoacoustics very well. The position, length and hydraulic radius of the refrigerator are optimized for the maximum total COP. The prime mover efficiency, refrigerator COP and dimensionless dissipation and their impacts on total COP are investigated and discussed. The results indicate that a COP of... 

Owing to the local nature of voltage and reactive power control, the voltage control is managed in a zonal or regional basis. A new comprehensive scheme for optimal selection of pilot points is proposed in this study. The uncertainties of operational and topological disturbances of the power system are included to provide the robustness of the pilot node set. To reduce the huge number of probable states (i.e. combined states of load and topological changes), a scenario reduction technique is used. The resulted optimal control problem is solved using a new immune-based genetic algorithm. The performance of the proposed method is verified over IEEE 118-bus and realistic Iranian 1274-bus... 

In this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. CGAM problem, a benchmark in cogeneration systems, is chosen as a case study. Thermodynamic model includes precise modeling of the whole plant. For simulation of the steady sate behavior, the static neural network is applied. Then using dynamic neural network, plant is optimized thermodynamically. Multi- layer feed forward neural networks is chosen as static net and recurrent neural networks as dynamic net. The steady state behavior of Excellent CGAM problem is simulated by MFNN. Subsequently, it is optimized by dynamic net. Results of static net have excellent... 

Feature relevance estimation is one of the most successful techniques used for improving the retrieval results of a content-based image retrieval (CBIR) system based on users' feedbacks. In this class of approaches, the weights of the feature elements (FEs) are adjusted based on the relevance feedbacks (RFs) given by the users to reduce the so-called semantic gap in the underlying CBIR system. An analytical approach is proposed in this paper to convert the users' feedbacks to the appropriate FE weights by solving a constrained optimization problem. Experiments on a set of 11,000 images from the Corel database show that the proposed approach outperforms other existing short-term RF approaches... 

The purpose of this study was to develop a computational model to simulate the dynamics of intraocular gas behavior in pneumatic retinopexy (PR) procedure. The presented model predicted intraocular gas volume at any time and determined the tolerance angle within which a patient can maneuver and still gas completely covers the tear(s). Computational fluid dynamics calculations were conducted to describe PR procedure. The geometrical model was constructed based on the rabbit and human eye dimensions. SF6 in the form of pure and diluted with air was considered as the injected gas. The presented results indicated that the composition of the injected gas affected the gas absorption rate and gas... 

We study a system of ordinary differential equations which describes the metapopulation SIR model. The main target is to control the epidemic spreading using the structure of connections between cities. For this purpose, we formulate optimal control strategy that the control represents a drug treatment and Prevention strategies . Some methods are given in numerical example section such as control through spectral radius of movement matrix or optimal control through travelling between cities. Existence results for the optimal control are studied  

Application of Cogeneration systems based gas turbine for heat and power production is increasing. Because of finite natural energy resources and increasing energy demand the cost effective design of energy systems is essential. CGAM problem as a cogeneration system is considered here for analyzing. Two new approaches are considered, first in thermodynamic model of gas turbine and cogeneration system considering blade cooling of gas turbine and second using genetic algorithm for optimization. The problem has been optimized from thermodynamic and thermoeconomic view point. Results show that Turbine Inlet Temperature (TIT) in thermodynamic optimum condition is higher than thermoeconomic one,... 

Based on the optimal control theory, the present study proposes a novel approach to derive a cooperative guidance law for two pursuers with an arbitrary-order linear dynamics against one zero-lag evader with random step maneuver. This approach is intended to minimize the mean value of the resultant control effort taken over a set of possible evader maneuvers which is modeled as a step function, the parameters of which are unknown. Since the resultant control effort is the minimum effort among the pursuers, we encounter the nonlinear "min" function in the performance index. By introducing binary parameters, it is changed to a linear function including binary parameters and continuous...