Search results for " optimization."
showing 10 items of 2333 documents
Frequency constrained optimal Power Flow based on Glow-worm Swarm Optimization in Islanded Microgrids
2015
This work presents an application of a swarm optimization method to solve the optimal power flow problem taking into account the constraints of frequency and line ampacity in three-phase islanded Microgrids. Each generation unit is equipped with a Power Electronics Interface. In the considered formulation, the droop control parameters are considered as variables to be adjusted by a higher control level, while the frequency is kept in rated bounds. Another typical constraint for OPF formulation, the max ampacity of each line, is also considered. Two case studies with different dimensions and electrical features have been considered and the obtained results show the efficiency of the proposed…
Multi-scenario multi-objective robust optimization under deep uncertainty: A posteriori approach
2021
This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results obtained with the novel approach to those obtained with previously used approaches. We show that the novel approach guarantees the feasibility and robust efficiency of the produced solutions under all selected scenarios, while decreasing computation cost, addresses the scenario-dependency issues, and enables the decision-makers to explore the trade-off …
An improved sampling strategy based on trajectory design for application of the Morris method to systems with many input factors
2012
[EN] In this paper, a revised version of the Morris approach, which includes an improved sampling strategy based on trajectory design, has been adapted to the screening of the most influential parameters of a fuzzy controller applied to WWTPs. Due to the high number of parameters, a systematic approach has been proposed to apply this improved sampling strategy with low computational demand. In order to find out the proper repetition number of elementary effects of each input factor on model output (EEi) calculations, an iterative and automatic procedure has been applied. The results show that the sampling strategy has a significant effect on the parameter significance ranking and that rando…
An Analysis of Bilevel Linear Programming Solving Parameters Based on Factoraggregation Approach
2013
We introduce the notion of factoraggregation,which is a special construction of general aggregation operators, and apply it for an analysis of optimal solution parameters for bilevel linear programming problems. The aggregation observes lower level objective functions considering the classes of equivalence generated by an objective function on the upper level. The proposed method is illustrated with numerical and graphical examples.
Fast Convergence of Neural Networks by Application of a New Min-Max Algorithm
1992
Abstract The paper presents a new application of the min-max method, an original algorithm previously successfully applied in other areas and based on a combination of the quasi-Newton and steepest descent methods in order to find the weights minimising the error function of a feed forward neural networks. Preliminary results, obtained by applying the proposed method to a simple 2-2-1 architecture on small Boolean learning problems, are very promising.
A New Min-Max Optimisation Approach for Fast Learning Convergence of Feed-Forward Neural Networks
1993
One of the most critical aspect for a wide use of neural networks to real world problems is related to the learning process which is known to be computational expensive and time consuming.
Approximation of the Feasible Parameter Set in worst-case identification of Hammerstein models
2005
The estimation of the Feasible Parameter Set (FPS) for Hammerstein models in a worst-case setting is considered. A bounding procedure is determined both for polytopic and ellipsoidic uncertainties. It consists in the projection of the FPS of the extended parameter vector onto suitable subspaces and in the solution of convex optimization problems which provide Uncertainties Intervals of the model parameters. The bounds obtained are tighter than in the previous approaches. hes.
Conflict resolution in the multi-stakeholder stepped spillway design under uncertainty by machine learning techniques
2021
Abstract The optimal spillway design is of great significance since these structures can reduce erosion downstream of the dams. This study proposes a risk-based optimization framework for a stepped spillway to achieve an economical design scenario with the minimum loss in hydraulic performance. Accordingly, the stepped spillway was simulated in the FLOW-3D® model, and the validated model was repeatedly performed for various geometric states. The results were used to form a Multilayer Perceptron artificial neural network (MLP-ANN) surrogate model. Then, a risk-based optimization model was formed by coupling the MLP-ANN and NSGA-II. The concept of conditional value at risk (CVaR) was utilized…
A Novel Mathematical Model For TLCD: Theoretical And Experimental Investigations
2014
In this paper, a novel mathematical model for the Tuned Liquid Column Damper (TLCD) is presented. Taking advantages of fractional derivatives and related concepts, a new equation of motion of the liquid inside the TLCD is obtained. Experimental laboratory tests have been performed in order to validate the proposed linear fractional formulation. Comparison among experimental results, numerical obtained using the classical formulation and numerical with the new linear fractional formulation are reported. Results in frequency domain show how the new linear fractional formulation can predict the real behavior of such a passive vibration control system, more correctly than the classical mathemat…
Passivity-based output feedback control of Markovian jump systems with discrete and distributed time-varying delays
2013
In this article, we present a new method in designing mode-dependent passivity-based output feedback controllers for Markovian jump systems with time-varying delays. Both discrete and distributed delays are considered in the model. A Lyapunov–Krasovskii function is constructed to establish new required sufficient conditions for ensuring exponentially mean-square stability and the passivity criteria, simultaneously. The method produces linear matrix inequality formulation that allows obtaining controller gains based on a convex optimisation method. Finally, a numerical example is given to illustrate the effectiveness of our approach.