Search results for " optimization."
showing 10 items of 2333 documents
A Novel Computational Approach for Harmonic Mitigation in PV Systems with Single-Phase Five-Level CHBMI
2018
In this paper, a novel approach to low order harmonic mitigation in fundamental switching frequency modulation is proposed for high power photovoltaic (PV) applications, without trying to solve the cumbersome non-linear transcendental equations. The proposed method allows for mitigation of the first-five harmonics (third, fifth, seventh, ninth, and eleventh harmonics), to reduce the complexity of the required procedure and to allocate few computational resource in the Field Programmable Gate Array (FPGA) based control board. Therefore, the voltage waveform taken into account is different respect traditional voltage waveform. The same concept, known as “voltage cancelation”, used for single-…
Continuous-Variable Instantaneous Quantum Computing is Hard to Sample
2017
Instantaneous quantum computing is a sub-universal quantum complexity class, whose circuits have proven to be hard to simulate classically in the Discrete-Variable (DV) realm. We extend this proof to the Continuous-Variable (CV) domain by using squeezed states and homodyne detection, and by exploring the properties of post-selected circuits. In order to treat post-selection in CVs we consider finitely-resolved homodyne detectors, corresponding to a realistic scheme based on discrete probability distributions of the measurement outcomes. The unavoidable errors stemming from the use of finitely squeezed states are suppressed through a qubit-into-oscillator GKP encoding of quantum information,…
Benchmarking parameter-free AMaLGaM on functions with and without noise.
2013
We describe a parameter-free estimation-of-distribution algorithm (EDA) called the adapted maximum-likelihood Gaussian model iterated density-estimation evolutionary algorithm (AMaLGaM-ID[Formula: see text]A, or AMaLGaM for short) for numerical optimization. AMaLGaM is benchmarked within the 2009 black box optimization benchmarking (BBOB) framework and compared to a variant with incremental model building (iAMaLGaM). We study the implications of factorizing the covariance matrix in the Gaussian distribution, to use only a few or no covariances. Further, AMaLGaM and iAMaLGaM are also evaluated on the noisy BBOB problems and we assess how well multiple evaluations per solution can average ou…
Optimal Impulse Control Problems and Linear Programming
2009
Optimal impulse control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions. In this paper, we identify a special class of optimal impulse control problems which are easy to solve. Easy to solve means that solution algorithms are polynomial in time and therefore suitable to the on-line implementation in real-time problems. We do this by using a paradigm borrowed from the Operations Research field. As main result, we present a solution algorithm that converges to the exact solution in polynomial time. Our approach consists in approximating the optimal impulse control problem via a binary linear programming proble…
The use of Markovian metapopulation models: a comparison of three methods reducing the dimensionality of transition matrices.
2001
The use of Markovian models is an established way for deriving the complete distribution of the size of a population and the probability of extinction. However, computationally impractical transition matrices frequently result if this mathematical approach is applied to natural populations. Binning, or aggregating population sizes, has been used to permit a reduction in the dimensionality of matrices. Here, we present three deterministic binning methods and study the errors due to binning for a metapopulation model. Our results indicate that estimation errors of the investigated methods are not consistent and one cannot make generalizations about the quality of a method. For some compared o…
Bluetooth Base Station Minimal Deployment for High Definition Positioning
2005
This paper discusses our approach to the problem of arranging a Bluetooth based positioning system capable of providing people coordinates in a given area with an accuracy as high as possible. Our strategy focuses on optimizing the disposition of a minimal number of available Bluetooth base stations in a subset of locations which are the only ones permitted by site characteristics and constraints. We used a genetic algorithm to this purpose and a layout chromosome whose best evolution suggested us how to deploy a minimal set of Bluetooth base stations. As a case study, we discuss our experiments and results which deal with a late middle age castle in Sicily where we carried out many trials.
New facets and an enhanced branch-and-cut for the min-max K -vehicles windy rural postman problem
2011
[EN] The min-max windy rural postman problem is a multiple vehicle version of the windy rural postman problem, WRPP, which consists of minimizing the length of the longest route to find a set of balanced routes for the vehicles. In a previous paper, an ILP formulation and a partial polyhedral study were presented, and a preliminary branch-and-cut algorithm that produced some promising computational results was implemented. In this article, we present further results for this problem. We describe several new facet-inducing inequalities obtained from the WRPP, as well as some inequalities that have to be satisfied by any optimal solution. We present an enhanced branch-and-cut algorithm that t…
A distributed minimum losses optimal power flow for islanded microgrids
2017
Abstract In this work, the minimum losses optimal power dispatch problem for islanded microgrids with distributed energy resources (DER) is solved by means of a distributed heuristic approach. Optimal power management is performed almost in real time, with a predefined schedule, i.e. every 5 min, and the solution is applied to generators when the current operating solution violates voltage or current constraints or when the current configuration produces too large power losses. The operating point of both inverter-interfaced generation units as well as rotating production systems can be modified simply using local information. The latter are voltage measurements and power injections or load…
A Perturbation Approach to Continuous-Time Portfolio Selection Under Stochastic Investment Opportunities
2013
This paper studies portfolio selection in continuous-time models with stochastic investment opportunities. We consider asset allocation problems where preferences are specified as power utility derived from terminal wealth as well as consumption-savings problems with recursive utility Epstein-Zin preferences. The paper approximates the associated dynamic programming problem by perturbing the coefficients of the stochastic dynamics. We represent the Hamilton-Jacobi-Bellman equation as a series of partial differential equations that can be solved iteratively in closed-form through computer algebra software, at any desired accuracy.
DECISION-MAKING MODELS FOR PREDICTIVE MAINTENANCE SERVICE SUPPORT SYSTEMS
2023
Nell'era digitale, la tecnologia è in continua evoluzione, con enormi progressi nell'automazione che consentono una gestione della manutenzione più efficiente ed economica. Le tecnologie digitali stanno convergendo e avanzando insieme alle industrie, determinando progressi significativi nella gestione della manutenzione. La tradizionale strategia di manutenzione preventiva gestita dall'uomo lascia progressivamente spazio alla manutenzione predittiva, che rappresenta un’ottima opportunità per migliorare significativamente la pianificazione della manutenzione del sistema, in particolare per i sistemi più complessi e dal significativo valore monetario. Tuttavia, l’implementazione di tecniche d…