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optimization-algorithms
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Total 249 records
Hydrodynamic optimization of marine propeller using gradient and non-gradientbased algorithms
, Article Acta Polytechnica Hungarica ; Volume 10, Issue 3 , 2013 , Pages 221-237 ; 17858860 (ISSN) ; Mazaheri, K ; Sharif University of Technology
2013
Abstract
Here a propeller design method based on a vortex lattice algorithm is developed, and two gradient-based and non-gradient-based optimization algorithms are implemented to optimize the shape and efficiency of two propellers. For the analysis of the hydrodynamic performance parameters, a vortex lattice method was used by implementing a computer code. In the first problem, one of the Sequential Unconstraint Minimization Techniques (SUMT) is employed to minimize the torque coefficient as an objective function, while keeping the thrust coefficient constant as a constraint. Also, chord distribution is considered as a design variable, namely 11 design variables. In the second problem, a modified...
A new experimental and theoretical approach for viscosity Iranian heavy crude oils based on tuning friction theory and friction volume theory parameters
, Article Inorganic Chemistry Communications ; Volume 139 , 2022 ; 13877003 (ISSN) ; Jafari Behbahani, T ; Ghotbi, C ; Sharif University of Technology
Elsevier B.V
2022
Abstract
In this research work, Friction Theory and Free Volume Theory are applied to live oil characterized based on SARA TEST for viscosity modeling and make a new model in combination with two equation of state (PR and PC-SAFT). Parameters for pseudo-components are obtained by tuning the viscosity at atmospheric pressure and temperatures of 10, 20, and 40 ℃. A new fitting approach is suggested where the number of fitting parameters is 17 and 12 for FT and FVT model, respectively. These parameters are tuned using the Genetic Algorithm and Particle Swarm Optimization and make eight new models. The results show that PC-SAFT provides viscosity predictions for all models with less deviation from...
Reducing energy consumption in iot by a routing whale optimization algorithm
, Article Malaysian Journal of Computer Science ; Volume 35, Issue 2 , 2022 , Pages 142-157 ; 01279084 (ISSN) ; Movaghar, A ; Motameni, H ; Barzegar, B ; Sharif University of Technology
Faculty of Computer Science and Information Technology
2022
Abstract
The Internet of Things is a new concept in the world of information and communication technology, in which for each being (whether it be a human, an animal or an object), the possibility of sending and receiving data through communication networks such as the Internet or Intranet is provided. Wireless sensors have limited energy resources due to their use of batteries in supplying energy, and since battery replacement in these sensors is not usually feasible, the longevity of wireless sensor networks is limited. Therefore, reducing the energy consumption of the used sensors in IoT networks to increase the network lifetime is one of the crucial challenges and parameters in such networks. In...
Simulated annealing optimization in wavefront shaping controlled transmission
, Article Applied Optics ; Volume 57, Issue 21 , 2018 , Pages 6233-6242 ; 1559128X (ISSN) ; Mohammadian, N ; Salimi, F ; Fatima, A ; Rahimi Tabar, M. R ; Nasiri Avanaki, M. R ; Sharif University of Technology
OSA - The Optical Society
2018
Abstract
In this research, we present results of simulated annealing (SA), a heuristic optimization algorithm, for focusing light through a turbid medium. Performance of the algorithm on phase and amplitude modulations has been evaluated. A number of tips to tune the optimization parameters are provided. The effect of measurement noise on the performance of the SA algorithm is explored. Additionally, SA performance is compared with continuous sequential and briefly with other optimization algorithms. © 2018 Optical Society of America
Ant colony algorithm for the shortest loop design problem [electronic resource]
, Article Computers and Industrial Engineering, Elsevier ; Volume 50, Issue 4, August 2006, Pages 358–366 ; Kazemi, Morteza ; Sharif University of Technology
Abstract
In this paper, a new algorithm for solving the shortest loop design problem is presented. The shortest loop design problem is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. In this paper, first it is shown that this problem can be represented as a graph model. The properties of the presented model enable us to design a meta-heuristic based on ant colony system algorithm for solving the shortest loop design problem. Computational results show the efficiency of our algorithm in compare to the other techniques
An evolutionary optimizing approach to neural network architecture for improving identification and modeling of aircraft nonlinear dynamics
, Article Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering ; Vol. 228, issue. 12 , 2014 , p. 2178-2191 ; Saghafi, F ; Sharif University of Technology
Abstract
In this paper, modified genetic algorithm has been used as a simultaneous optimizer of recurrent neural network to improve identification and modeling of aircraft nonlinear dynamics. Weighted connections, network architecture, and learning rules are features that play important roles in the quality of neural networks training and their generalizability in order to model nonlinear systems. Therefore, the main focus of this paper is to apply appropriate evolutionary methods in order to simultaneously optimize the parameters of neural networks for the improvement identification and modeling of aircraft nonlinear dynamics. To validate this study, the results have been compared with the recorded...
Symbiotic evolution to avoid linkage problem
, Article Studies in Computational Intelligence ; Volume 157 , 2008 , Pages 285-314 ; 1860949X (ISSN) ; 9783540850670 (ISBN) ; Bagheri Shouraki, S ; Sharif University of Technology
2008
Abstract
In this chapter, we introduce Symbiotic Evolutionary Algorithm (SEA) as a template for search and optimization based on partially specified chromosomes and symbiotic combination operator. We show that in contrast to genetic algorithms with traditional recombination operators, this template will not be bound to linkage problems. We present three implementations of this template: first, as a pure algorithm for search and optimization, second, as an artificial immune system, and third, as an algorithm for classifier rule base evolution, and compare implementation results and feature lists with similar algorithms. © 2008 Springer-Verlag Berlin Heidelberg
Symbiotic tabu search
, Article 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007, London, 7 July 2007 through 11 July 2007 ; 2007 , Pages 1515- ; 1595936971 (ISBN); 9781595936974 (ISBN) ; Bagheri Shouraki, S ; Jafari Jashmi B ; Jalali Heravi, M ; Sharif University of Technology
2007
Abstract
Recombination in the Genetic Algorithm (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations hopefully producing an offspring that has the good characteristics of both parents. Symbiotic Combination is formerly introduced as an alternative for sexual recombination operator to overcome the need of explicit design of recombination operators in GA all. This paper presents an optimization algorithm based on using this operator in Tabu Search. The algorithm is benchmarked on two problem sets and is compared with standard genetic algorithm and symbiotic evolutionary adaptation model, showing success rates higher than both cited...
Well placement optimization using a particle swarm optimization algorithm, a novel approach
, Article Petroleum Science and Technology ; Vol. 32, issue. 2 , 2014 , pp. 170-179 ; ISSN: 10916466 ; Pishvaie, M. R ; Aminshahidy, B ; Sharif University of Technology
Abstract
Optimal well placement is a crucial step in reservoir development process. The key points in such an optimization process are using a fast function evaluation tool and development of an efficient optimization algorithm. This study presents an approach that uses particle swarm optimization algorithm in conjunction with streamline simulation to determine the optimum well locations within a reservoir, regarding a modified net present value as the objective. Performance of this algorithm was investigated through several different examples, and compared to that of genetic algorithm (GA) and simulated annealing (SA) methods. It was observed that particle swarm optimization algorithm outperformed...
Semi-active vibration control of an eleven degrees of freedom suspension system using neuro inverse model of magnetorheological dampers
, Article Journal of Mechanical Science and Technology ; Volume 26, Issue 8 , 2012 , Pages 2459-2467 ; 1738494X (ISSN) ; Abbasi, M ; Mahdavi, H ; Osgouie, K. G ; Sharif University of Technology
Springer
2012
Abstract
A semi-active controller-based neural network for a suspension system with magnetorheological (MR) dampers is presented and evaluated. An inverse neural network model (NIMR) is constructed to replicate the inverse dynamics of the MR damper. The typical control strategies are linear quadratic regulator (LQR) and linear quadratic gaussian (LQG) controllers with a clipped optimal control algorithm, while inherent time-delay and non-linear properties of MR damper lie in these strategies. LQR part of LQG controller is also designed to produce the optimal control force. The LQG controller and the NIMR models are linked to control the system. The effectiveness of the NIMR is illustrated and...
Invariancy of sparse recovery algorithms
, Article IEEE Transactions on Information Theory ; Volume 63, Issue 6 , 2017 , Pages 3333-3347 ; 00189448 (ISSN) ; Sharifnassab, A ; Babaie Zadeh, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
In this paper, a property for sparse recovery algorithms, called invariancy, is introduced. The significance of invariancy is that the performance of the algorithms with this property is less affected when the sensing (i.e., the dictionary) is ill-conditioned. This is because for this kind of algorithms, there exists implicitly an equivalent well-conditioned problem, which is being solved. Some examples of sparse recovery algorithms will also be considered and it will be shown that some of them, such as SL0, Basis Pursuit (using interior point LP solver), FOCUSS, and hard thresholding algorithms, are invariant, and some others, like Matching Pursuit and SPGL1, are not. Then, as an...
Implementation of APSO and improved APSO on Non-cascaded and cascaded short term hydrothermal scheduling
, Article IEEE Access ; Volume 9 , 2021 , Pages 77784-77797 ; 21693536 (ISSN) ; Kashif, S. A. R ; Liaquat, S ; Rasool, A ; Padmanaban, S ; Iqbal, M. A ; Baig, M. A ; Khan, B ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
Short-term hydrothermal scheduling (STHTS) is a highly non-linear, multi-model, non-convex, and multi-dimensional optimization problem that has been worked upon for about 5 decades. Many research articles have been published in solving different test cases of STHTS problem, while establishing the superiority of one type of optimization algorithm over the type, in finding the near global best solution of these complex problems. This paper presents the implementation of an improved version of a variant of the Particle Swarm Optimization algorithm (PSO), known as Accelerated Particle Swarm Optimization (APSO) on three benchmark test cases of STHTS problems. The adaptive and variable nature of...
A mapreduce algorithm for metric anonymity problems
, Article 31st Canadian Conference on Computational Geometry, CCCG 2019, 8 August 2019 through 10 August 2019 ; 2019 , Pages 117-123 ; Ghodsi, M ; Miri, S ; Sharif University of Technology
Canadian Conference on Computational Geometry
2019
Abstract
We focus on two metric clusterings namely r-gather and (r, ?)-gather. The objective of r-gather is to minimize the radius of clustering, such that each cluster has at least r points. (r, ?)-gather is a version of r-gather with the extra condition that at most n? points can be left unclustered (outliers). MapReduce is a model used for processing big data. In each round, it distributes data to multiple servers, then simultaneously processes each server's data. We prove a lower bound 2 on the approximation factor of metric r-gather in the MapReduce model, even if an optimal algorithm for r-gather exists. Then, we give a (4+ δ)-approximation algorithm for r-gather in MapReduce which runs in O(...
A mapreduce algorithm for metric anonymity problems
, Article 31st Canadian Conference on Computational Geometry, CCCG 2019, 8 August 2019 through 10 August 2019 ; 2019 , Pages 117-123 ; Ghodsi, M ; Miri, S ; Sharif University of Technology
Canadian Conference on Computational Geometry
2019
Abstract
We focus on two metric clusterings namely r-gather and (r, ?)-gather. The objective of r-gather is to minimize the radius of clustering, such that each cluster has at least r points. (r, ?)-gather is a version of r-gather with the extra condition that at most n? points can be left unclustered (outliers). MapReduce is a model used for processing big data. In each round, it distributes data to multiple servers, then simultaneously processes each server's data. We prove a lower bound 2 on the approximation factor of metric r-gather in the MapReduce model, even if an optimal algorithm for r-gather exists. Then, we give a (4+ δ)-approximation algorithm for r-gather in MapReduce which runs in O(...
Dynamic optimization in chemical processes using region reduction strategy and Control Vector Parameterization with an Ant Colony Optimization algorithm
, Article Chemical Engineering and Technology ; Volume 31, Issue 4 , 2008 , Pages 507-512 ; 09307516 (ISSN) ; Pishvaie, M. R ; Sharif University of Technology
2008
Abstract
Two different approaches of the dynamic optimization for chemical process control engineering applications are presented. The first approach is based on discretizing both the control region and the time interval. This method, known as the Region Reduction Strategy (RRS), employs the previous solution in its next iteration to obtain more accurate results. Moreover, the procedure will continue unless the control region becomes smaller than a prescribed value. The second approach is called Control Vector Parameterization (CVP) and appears to have a large number of advantages. In this approach, control action is generated in feedback form, i.e., a set of trial functions of the state variables...
Tuning of novel fractional order fuzzy PID controller for automatic voltage regulator using grasshopper optimization algorithm
, Article Majlesi Journal of Electrical Engineering ; Volume 15, Issue 2 , 2021 , Pages 39-45 ; 2345377X (ISSN) ; Hadi, M. B ; Manthouri, M ; Sharif University of Technology
Islamic Azad University
2021
Abstract
One of the essential pieces of equipment in the power system is the Automatic Voltage Regulator (AVR) or synchronous generator excitation. The system's goal is to maintain the terminal voltage of the synchronous generator at the desired level. AVR is inherently uncertain. Hence, the proposed controller should be able to handle the problem. In this paper, Fractional Order Fuzzy PID (FOFPID) controller has been employed to control the system. To enhance the controller's performance, the Grasshopper Optimization Algorithm (GOA) is used to tune the controller's parameters. Unlike other methods, the FOFPID controller gains are not constant and alter in different operating conditions. The...
Optimization of Endurance Time Acceleration Function using Fourier and Wavelet Transform and Optimization Algorithms
, M.Sc. Thesis Sharif University of Technology ; Esmaeil Purestekanchi, Homayoon (Supervisor)
Abstract
So far, several studies have been conducted on the endurance time method. In general, these studies can be categorized into two categories. The first group of studies are based on the theoretical foundations of this methodology and the second group of researches that use the method of endurance time in different engineering issues of earthquake and engineering, and also compare the results of this method with other conventional methods of seismic analysis.The purpose of this study, which is more in the first category of research, is to optimize the acceleration functions using various Transform, such as Fourier and Wavelet, as well as the use of various optimization algorithms. In optimizing...
Prediction of Crude Oil Viscosity Using Equations of State
, M.Sc. Thesis Sharif University of Technology ; Ghotbi, Sirous (Supervisor) ; Jafari behbahani, Traneh (Supervisor)
Abstract
experimental data of crude oil for viscosity are available in limited conditions of temperature and pressure. Therefore, the use of empirical equations and relations to predict it at temperatures and pressures beyond the temperature and pressure of the reservoir is inevitable. In order to reduce the cost of the laboratory, the use of a comprehensive model in this project is considered. For this purpose, using two theories of friction and free volume, the Peng Robinson and PC-SAFT equation of states and genetic algorithms and particle swarm optimization are widely used to calculate the viscosity of pure hydrocarbons, binary mixtures of hydrocarbons and crude oil have been used. Obviously, by...
Localization Optimization: A Customized Cuckoo approach on DV-Hop Algorithm
, M.Sc. Thesis Sharif University of Technology ; Hemmatyar, Ali Mohammad Afshin (Supervisor) ; Mazinani, Majid (Supervisor)
Abstract
Node localization is an important issue in dynamic environments for location-dependent applications of Wireless Sensor Networks (WSNs). Geographical location information is necessary in many WSN applications. The goal of localization algorithm is to assign geographical coordinates to each unknown node position. Among different localization algorithms, DV-hop is one of the well- known algorithms. DV-hop algorithm is a range-free algorithm and has significant error in node location estimation. Since the node deployment is stochastic, minimizing this error has a critical role in location estimation accuracy of the algorithm. Increasing communication radius and number of anchors, to the certain...
A Library For Developing Optimization Algorithms In Metabolic Network Analysis
, M.Sc. Thesis Sharif University of Technology ; Tefagh, Mojtaba (Supervisor)
Abstract
In systems biology, one of the most important biological systems that is analyzed and investigated is the metabolic network. A metabolic network is a complete set of metabolic and physical processes that determine the physiological and biochemical characteristics of a cell. These networks encompass metabolic chemical reactions, metabolic pathways, and regulatory interactions that govern these reactions. Therefore, metabolic networks at the genome scale are immensely large, making even efficient algorithms time-consuming for their analysis. To address this issue, reducing metabolic networks is crucial, as it significantly decreases the execution time of algorithms and enhances computational...