Search results for "Optimization methods"
showing 10 items of 12 documents
OPKINE, a multipurpose program for kinetics
1991
The program OPKINE is presented for the study of reaction mechanisms and multicomponent analysis in dynamic conditions. This program is written in FORTRAN-77 for IBM 30/90 and VAX 8300 computers, and permits the simultaneous evaluation of both rate constants and initial reagent concentrations or, alternatively, rate constants and sensitivities. Up to 20 kinetic curves, with up to 400 points each, can be treated to evaluate up to 40 parameters. Integration of the system of differential equations is performed by means of the Runge–Kutta–Fehlberg method. OPKINE is provided with the Simplex, and modified versions of the Davidon–Fletcher–Powell and Gauss–Newton–Marquardt optimization methods. A …
Improving programming skills of Mechanical Engineering students by teaching in C# multi-objective optimizations methods
2017
Designing an optimized suspension system that meet the main functions of comfort, safety and handling on poor quality roads is a goal for researchers. This paper represents a software development guide for designers of suspension systems with less programming skills that will enable them to implement their own optimization methods that improve traditional methods by using their domain knowledge.
mplicit Identification of Contact Parameters in a Continuous Chain Model
2011
Accurate contact modeling is of great importance in the field of dynamic chain simulations. In this paper emphasis is on contact dynamics for a time-domain simulation model of large chains guided in a closed loop track. The chain model is based on theory for unconstrained rigid multibody dynamics where contact within the chain and with the track is defined through continuous point contacts using the contact indentation and rate as means. This paper presents an implicit method to determine contact parameters of the chain model through the use of none gradient optimization methods. The set of model parameters are estimated by minimizing the residual between simulated and measured results. The…
An Approach to the Automatic Comparison of Reference Point-Based Interactive Methods for Multiobjective Optimization
2021
Solving multiobjective optimization problems means finding the best balance among multiple conflicting objectives. This needs preference information from a decision maker who is a domain expert. In interactive methods, the decision maker takes part in an iterative process to learn about the interdependencies and can adjust the preferences. We address the need to compare different interactive multiobjective optimization methods, which is essential when selecting the most suited method for solving a particular problem. We concentrate on a class of interactive methods where a decision maker expresses preference information as reference points, i.e., desirable objective function values. Compari…
On the integration of kinetic models using a high-order taylor series method
1992
A general equation to derive kinetic models up to any order is given. This equation greatly facilitates the application of the Taylor series method to the integration of kinetic models up to very high orders. When dealing with non-stiff models, computing time is always reduced by increasing the integration order, at least up to the 20th order. When the model is stiff, the integration order should be optimized; however, a twelfth order is recommended to integrate weakly stiff models. The use of an algorithm which permits the immediate calculation of the integration step size required to maintain a given accuracy leads to further reductions in computing time. When implemented as recommended h…
Voltage Regulation and Power Losses Minimization in Automated Distribution Networks by an Evolutionary Multiobjective Approach
2004
In this paper, the problem of voltage regulation and power losses minimization for automated distribution systems is dealt with. The classical formulation of the problem of optimal control of shunt capacitor banks and Under Load Tap Changers located at HV/MV substations has been coupled with the optimal control of tie-switches and capacitor banks on the feeders of a large radially operated meshed distribution system with the aim of attaining minimum power losses and the flattening of the voltage profile. The considered formulation requires the optimization of two different objectives; therefore the use of adequate multiobjective heuristic optimization methods is needed. The heuristic strate…
A Methodology for Solving the Multiple Criteria Macroeconomic Policy Problem
1983
In this paper we review the results of our research on using interactive multiple criteria optimization methods for solving macroeconomic policy problems in Finland. An existing econometric model describing the interrelationships between different variables and sectors of the economy is used. In addition, the current status of the implementation work is reported and some possibilities for future research are discussed.
ANOVA-MOP: ANOVA Decomposition for Multiobjective Optimization
2018
Real-world optimization problems may involve a number of computationally expensive functions with a large number of input variables. Metamodel-based optimization methods can reduce the computational costs of evaluating expensive functions, but this does not reduce the dimension of the search domain nor mitigate the curse of dimensionality effects. The dimension of the search domain can be reduced by functional anova decomposition involving Sobol' sensitivity indices. This approach allows one to rank decision variables according to their impact on the objective function values. On the basis of the sparsity of effects principle, typically only a small number of decision variables significantl…
Application to an italian distribution system of a multiobjective optimal Volt/VAR control strategy: improvements and management problems
2007
In this paper, the experiences and results deriving from the application of a multiobjective optimal management strategy to a distribution network supplying an area in province of Palermo, Italy, are presented. The adopted strategy allows, through the interventions on the Under Load Tap Changers (ULTC) of the primary substations and on tie-switches, to reduce power losses and improve the voltage profiles. To solve the optimization problem, an evolutionary approach has been adopted; it employs fuzzy logic for an adequate and simultaneous fulfilment of the different objectives. The application section presents a deep technical and economical analysis of the results attained, applying the opti…
Optimization of Delayed-State Kalman-Filter-based Algorithm via Differential Evolution for Sensorless Control of Induction Motors
2010
This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components as mathematical model and the stator-voltage equations as observation model so that only a vector of four variables has to be offline optimized. Numerical results, carried out using a low-speed training test, show that the proposed DE-based approach is very promising and clearly outperforms a cla…