Search for: constrained-optimization
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    A feature relevance estimation method for content-based image retrieval

    , Article International Journal of Information Technology and Decision Making ; Volume 10, Issue 5 , 2011 , Pages 933-961 ; 02196220 (ISSN) Ajorloo, H ; Lakdashti, A ; Sharif University of Technology
    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... 

    On the coupled continuous knapsack problems: projection onto the volume constrained Gibbs N-simplex

    , Article Optimization Letters ; Volume 10, Issue 1 , 2016 , Pages 137-158 ; 18624472 (ISSN) Tavakoli, R ; Sharif University of Technology
    Springer Verlag  2016
    Coupled continuous quadratic knapsack problems (CCK) are introduced in the present study. The solution of a CCK problem is equivalent to the projection of an arbitrary point onto the volume constrained Gibbs N-simplex, which has a wide range of applications in computational science and engineering. Three algorithms have been developed in the present study to solve large scale CCK problems. According to the numerical experiments of this study, the computational costs of presented algorithms scale linearly with the problem size, when it is sufficiently large. Moreover, they show competitive or even superior computational performance compared to the advanced QP solvers. The ease of... 

    Multi-objective non-linear fixed charge transportation problem with multiple modes of transportation in crisp and interval environments

    , Article Applied Soft Computing Journal ; Volume 80 , 2019 , Pages 628-649 ; 15684946 (ISSN) Biswas, A ; Shaikh, A. A ; Akhavan Niaki, S. T ; Sharif University of Technology
    Elsevier Ltd  2019
    This paper aims to propose an approach based on NSGA-II for solving multi-objective non-linear fixed charge transportation problem with multiple modes of transport in crisp and interval environments. Certain modifications need to be made in the existing NSGA-II configuration to calculate the crowding distance of a solution in the interval environment. Besides, a crossover and a mutation scheme suitable for multiple modes of transportation are developed. In the end, a set of test problems are solved in both environments and some comparative studies are performed restricting the problem to only one mode of transport at a time. Finally, the results of the proposed algorithm are compared with... 

    Path Planning for a Mobil Robot in an Unkonwn Environment By Recurrent Neural Networks

    , M.Sc. Thesis Sharif University of Technology Hassanzadeh, Mohammad (Author) ; Zarei, Alireza (Supervisor) ; Malek, Alaeddin (Supervisor)
    Path planning of a robot inside an environment with obstacles is to determine an appropriate path for moving from an initial point to a destination without colliding the obstacles. The main considerations in selecting such a path are its length and simplicity in terms of links or turn angles. In this paper, we study this problem for a point robot in the plane and our goal is to minimize the path length. We solve this problem by converting it to an optimization problem and solving the resulted optimization problem by a recurrent neural network. According to the implementation results, the obtained path is a proper approximation of the minimum length path, especially when obstacles are not too... 

    Distributionally robust chance-constrained generation expansion planning

    , Article IEEE Transactions on Power Systems ; Volume 35, Issue 4 , 2020 , Pages 2888-2903 Pourahmadi, F ; Kazempour, J ; Ordoudis, C ; Pinson, P ; Hosseini, S. H ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    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,... 

    Interval Methods for Global Optimization

    , M.Sc. Thesis Sharif University of Technology Bedrosian, Narbeh (Author) ; Mahdavi Amiri, Nezameddin (Supervisor)
    We explain new interval methods, recently introduced in the literature, for solving unconstrained and constrained global optimization problems. The strategy is characterized by a subdivision of the argument intervals of the expression and a recomputation of the expression with these new intervals. By varying the selection and termination criteria, we explain new variants. These methods are used to solve problems with an objective function that has possibly a large number of local minima and constraints that may be nonlinear or nonconvex. We describe algorithms that return global minima and points at which the objective function is within a defined distance from the global minima. Numerical... 

    An Inexact Newton Method for Nonconvex Equality Constrained Optimization

    , M.Sc. Thesis Sharif University of Technology Mousavi, Ahmad (Author) ; Mahdavi Amiri, Nezamoddin (Supervisor)

    A Line Search Exact Penalty Method Using Steering Rules

    , M.Sc. Thesis Sharif University of Technology Dehghan Nayeri, Maryam (Author) ; Mahdavi Amiri, Nezamoddin (Supervisor)
    Exact linear search algorithm recently have been proposed in the literature by Byrd, Lopez-Calvaz and Nocedal for solving nonlinear programming problems. Line search algorithms for nonlinear programming problems must include safeguards to have global convergence properties. We explain an exact penalization approach that extends the class of problems that can be solved with line search SQP methods. In the algorithm, the penalty parameter is adjusted at every iteration to ensure sufficient progress in linear feasibilility and to promote acceptance of the step. A trust region is used to assist in the determination of the penalty parameter. It is shown that the algorithm enjoys favorable... 

    A First-Order Interior-Point Method For Linearly Constrained Smooth Optimization

    , M.Sc. Thesis Sharif University of Technology Ebadi Zadeh, Monireh (Author) ; Peyghami, Mohammad Reza (Supervisor) ; Fotouhi, Morteza (Supervisor)
    In this thesis, we propose a first-order interior-point method for linearly constrained smooth optimization which was recently proposed in the literatuare that unifies and extends first-order affine-scaling method and replicator dynamics method for standard quadratic programming. Global convergence and, in the case of quadratic program, the (sub)linear convergence rate and iterate convergence results are derived.The method is implemented and numerical experiments on simplex onstrained problems with 1000 variables is reported  

    Multimaterial topology optimization by volume constrained Allen-Cahn system and regularized projected steepest descent method

    , Article Computer Methods in Applied Mechanics and Engineering ; Vol. 276 , 2014 , pp. 534-565 ; ISSN: 00457825 Tavakoli, R ; Sharif University of Technology
    A new computational algorithm is introduced in the present study to solve multimaterial topology optimization problems. It is based on the penalization of the objective functional by the multiphase volume constrained Ginzburg-Landau energy functional. The update procedure is based on the gradient flow of the objective functional by a fractional step projected steepest descent method. In the first step, the new design is found based on the projected steepest descent method to ensure the reduction in the objective functional, simultaneously satisfying the control constraints. In the second step, regularization step, an H1 regularity of the solution is ensured while keeping the feasibility of... 

    On natural based optimization

    , Article Cognitive Computation ; Volume 2, Issue 2 , 2010 , Pages 97-119 ; 18669956 (ISSN) Nobakhti, A ; Sharif University of Technology
    Nature has always been a source of great inspiration for engineers and mathematicians. Evolutionary Algorithms are the latest in a line of natural-based innovations which have had a profound effect on the application of optimization in science and engineering. Although based on nature, Evolutionary Algorithms are nonetheless distinctly different from natural evolution in several areas. This paper outlines early and recent developments of Evolutionary Algorithms while covering those areas of difference. Practical issues related to the use of Evolutionary Algorithms, key parameters that affect the quality of the search and impact of user choices in problem formulation are also covered in this... 

    Structural optimization by spherical interpolation of objective function and constraints

    , Article Scientia Iranica ; Volume 23, Issue 2 , 2016 , Pages 548-557 ; 10263098 (ISSN) Meshki, H ; Joghataie, A ; Sharif University of Technology
    Sharif University of Technology  2016
    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... 

    Optimal design of multiphase composites under elastodynamic loading

    , Article Computer Methods in Applied Mechanics and Engineering ; Volume 300 , 2016 , Pages 265-293 ; 00457825 (ISSN) Tavakoli, R ; Sharif University of Technology
    Elsevier  2016
    An algorithm is proposed to optimize the performance of multiphase structures (composites) under elastodynamic loading conditions. The goal is to determine the distribution of material in the structure such that the time-averaged total stored energy of structure is minimized. A penalization strategy is suggested to avoid the checkerboard instability, simultaneously to generate near 0-1 topologies. As a result of this strategy, the solutions of presented algorithm are sufficiently smooth and possess the regularity of H1 function space. A simple method for the continuum adjoint sensitivity analysis of the corresponding PDE-constrained optimization problem is presented. It is general and can be... 

    Joint sum rate and error probability optimization: finite blocklength analysis

    , Article IEEE Wireless Communications Letters ; 2017 ; 21622337 (ISSN) Haghifam, M ; Mili, M. R ; Makki, B ; Nasiri Kenari, M ; Svensson, T ; Sharif University of Technology
    We study the tradeoff between the sum rate and the error probability in downlink of wireless networks. Using the recent results on the achievable rates of finite-length codewords, the problem is cast as a joint optimization of the network sum rate and the per-user error probability. Moreover, we develop an efficient algorithm based on the divide-and-conquer technique to simultaneously maximize the network sum rate and minimize the maximum users’ error probability and to evaluate the effect of the codeword length on the system performance. The results show that, in delay-constrained scenarios, optimizing the per-user error probability plays a key role in achieving high throughput. IEEE  

    Time-Sharing improves dynamic index coding delay

    , Article 2019 Iran Workshop on Communication and Information Theory, IWCIT 2019, 24 April 2019 through 25 April 2019 ; 2019 ; 9781728105840 (ISBN) Hadi, M ; Mojahedian, M. M ; Aref, M. R ; Pakravan, M. R ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    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  

    A conceptual structure for value based assessment of dynamic reactive power support in power markets

    , Article Electric Power Systems Research ; Volume 77, Issue 7 , 2007 , Pages 761-770 ; 03787796 (ISSN) Pirayesh, A ; Vakilian, M ; Feuillet, R ; Hadj Said, N ; Sharif University of Technology
    This paper presents a practical reactive power valuation method, for the purpose of the reactive power pricing, in which the VAr value is decomposed into two components. These components are basically different from those already employed in the literature. Using a security constrained optimization model, the proposed scheme allocates two specific amounts of MW transactions to each generator as a dynamic reactive power source. One of these allocated amounts represents the contribution of the VAr resource to the shipment of active power, while the other one represents the contribution to the protection of the system against voltage instability. The final VAr value is derived using the... 

    A Filter-Trust-Region Method for Simple-Bound Constrained Optimization

    , M.Sc. Thesis Sharif University of Technology Mehrali Varjani, Mohsen (Author) ; Mahdavi Amiri, Nezameddin (Supervisor)
    We explain a filter-trust-region algorithm for solving nonlinear optimization problems with simple bounds recently proposed by Sainvitu and Toint. The algorithm is shown to be globally convergent to at least one first-order critical point. We implement the algorithm and test the program on various problems. The results show the effectiveness of the algorithm  

    , M.Sc. Thesis Sharif University of Technology Dehghani, Saeed (Author) ; Haeri, Mohammad (Supervisor)
    Robust model predictive control(RMPC) is a control strategy that has been widely adopted in industry and academic researches.In this project we have modified robust nonlinear model predictive control using SOS and dynamic feedback. In this control strategy we will linearize the nonlinear model of the system about it’s operating point. We will consider the error of linearization as an uncertainty and find an upper bound for uncertainty. Then we will change control objective to minimizing this upper bound. The most advantage of changing the control objective is that nonlinear system results a non-convex optimization problem but this strategy terminates a convex optimization problem. To find... 

    Solving Nonlinear Systems of Mixed Iqualities and Inequalities Via Trust Region Quadratic Methods

    , M.Sc. Thesis Sharif University of Technology Ghasemi, Shojaeddin (Author) ; Razvan, Mohammad Reza (Supervisor) ; Payghami, Mohammad Reza (Supervisor)

    Control of Adaptive Optic Systems Using Transverse Actuators

    , M.Sc. Thesis Sharif University of Technology Rostam, Mohammad Reza (Author) ; Jalali, Mir Abbas (Supervisor)
    Turbulence can distort and corrupt the image in quite a few ways when light from a distance star or another astronomical object enters the Earth's atmosphere. It is inevitable that all images produced by any telescope on ther Earth are blurred by these distortions. Adaptive Optics is a technology used to improve the performance of optical systems by reducing the effect of wavefront distortions: it aims at correcting the deformations of an incoming wavefront by deforming a mirror in order to compensate for the distortion. The research work reported in this thesis presents a solution to the surface shape control problems in a Deformable Mirror system. Our first goal is to derive equations that...