Search results for "Optimization problem"
showing 10 items of 281 documents
Technical and Economical Analysis of Different Measures for Efficient Operation of a Distribution Network in a Mediterranean Island
2006
The paper performs a technical and economical comparison of different measures to improve the efficiency of a MV system for power distribution in the Mediterranean island of Lampedusa. The study takes into consideration three possible measures: 1) rated voltage increase from 10 kV to 20 kV; 2) reactive power compensation with fixed capacitor banks; 3) reactive power compensation with switchable capacitor banks. While the study of the first two considered measures is carried out with classical design methods, the optimal reactive design with switchable capacitor banks is carried out by means of a specific software set up at the DIEET and implementing the multiobjective optimization genetic a…
An Optimal Monitoring Program for Obtaining Voltage Sag System Indexes
2006
This paper presents a meter placement method for voltage sags monitoring in large transmission systems. An integer programming-based modeling is proposed for choosing the locations of power quality meters. A branch-and-bound-type algorithm is used to solve the optimization problem. A large transmission network is used to validate the method. Stochastic assessment of voltage sags is applied to the test network to obtain simulated monitoring results. Voltage sags system indexes are calculated from monitoring programs designed according to the optimization method. Comparisons with the system indexes obtained from a full monitoring program show the applicability of the method.
Friction Stir Welding Lap Joint Resistance Optimization Through Gradient Techniques
2007
In recent years, scientific interest on friction stir welding (FSW) has grown more and more since such a joining technique allows one to weld lightweight alloys that are rather difficult to weld or even “unweldable” with the classic fusion welding operations. Furthermore, few industrial applications of the process are already known in different manufacturing fields. In this paper, the optimization problem of a FSW lap joint for automotive applications is investigated, taking into account process parameters such as the tool rotating speed and the tool feed rate; a numerical gradient technique is applied for the optimization procedure reducing the number of experimental tests to be developed.
A neural network-based optimizing control system for a seawater-desalination solar-powered membrane distillation unit
2013
Abstract Several schemes have been proposed so far for coupling desalination processes with the use of renewable energy. One of their main drawbacks, however, is the nature of the energy source that requires a discontinuous and non-stationary operation, with some control and optimization problems. In the present work, a solar powered membrane distillation system has been used for developing an optimizing control strategy. A neural network (NN) model of the system has been trained and tested using experimental data purposely collected. Afterwards, the NN model has been used for the analysis of the process performance under various operating conditions, namely distillate production versus fee…
A New Time Dependent Model Based on Level Set Motion for Nonlinear Deblurring and Noise Removal
1999
In this paper we summarize the main features of a new time dependent model to approximate the solution to the nonlinear total variation optimization problem for deblurring and noise removal introduced by Rudin, Osher and Fatemi. Our model is based on level set motion whose steady state is quickly reached by means of an explicit procedure based on an ENO Hamilton-Jacobi version of Roe's scheme. We show numerical evidence of the speed, resolution and stability of this simple explicit procedure in two representative 1D and 2D numerical examples.
An Integrated fuzzy Cells-classifier
2006
The term soft-computing has been introduced by Zadeh in 1994. Soft-computing provides an appropriate paradigm to program malleable and smooth concepts. In this paper a genetic algorithm is proposed to fuse the classification results due to different distance functions. The combination is based on the optimization of a vote strategy and it is applied to cells classification.
Strategies for accelerating ant colony optimization algorithms on graphical processing units
2007
Ant colony optimization (ACO) is being used to solve many combinatorial problems. However, existing implementations fail to solve large instances of problems effectively. In this paper we propose two ACO implementations that use graphical processing units to support the needed computation. We also provide experimental results by solving several instances of the well-known orienteering problem to show their features, emphasizing the good properties that make these implementations extremely competitive versus parallel approaches.
Finding optimal finite biological sequences over finite alphabets: the OptiFin toolbox
2017
International audience; In this paper, we present a toolbox for a specific optimization problem that frequently arises in bioinformatics or genomics. In this specific optimisation problem, the state space is a set of words of specified length over a finite alphabet. To each word is associated a score. The overall objective is to find the words which have the lowest possible score. This type of general optimization problem is encountered in e.g 3D conformation optimisation for protein structure prediction, or largest core genes subset discovery based on best supported phylogenetic tree for a set of species. In order to solve this problem, we propose a toolbox that can be easily launched usin…
Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization
2014
Abstract Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Restricted Boltzmann Machines (RBMs) are generative neural networks with these desired properties. We integrate an RBM into an EDA and evaluate the performance of this system in solving combinatorial optimization problems with a single objective. We assess how the number of fitness evaluations and the CPU time scale with problem size and complexity. The results are compared to the Bayesian Optimization Algorithm (BOA), a state-of-the-art multivariate EDA, and the Dependency Tree Algorithm (DTA), which uses a simpler probability model requiring less computati…
A New Nonparametric Estimate of the Risk-Neutral Density with Applications to Variance Swaps
2021
We develop a new nonparametric approach for estimating the risk-neutral density of asset prices and reformulate its estimation into a double-constrained optimization problem. We evaluate our approach using the S\&P 500 market option prices from 1996 to 2015. A comprehensive cross-validation study shows that our approach outperforms the existing nonparametric quartic B-spline and cubic spline methods, as well as the parametric method based on the Normal Inverse Gaussian distribution. As an application, we use the proposed density estimator to price long-term variance swaps, and the model-implied prices match reasonably well with those of the variance future downloaded from the CBOE websi…