Parameter reconstructions are indispensable in metrology. Here, the objective is to explain K experimental measurements by fitting them a parameterized model of measurement process. The parameters regularly determined least-square methods, that is, minimizing sum squared residuals between predictions and observations, χ2. functions often involve computationally demanding numerical simulations. ...

We propose an algorithm to generate inner and outer polyhedral approximations the upper image of a bounded convex vector optimization problem. It is approximation based on solving norm-minimizing scalarizations. Unlike Pascoletti–Serafini scalarization used in literature for similar purposes, it does not involve direction parameter. Therefore, free direction-biasedness. also modification by int...

introduction: gene expression and purification of luciferases from the firefly, lampyris turkestanicus, and optimization of cellular atp measurements were performed. methods: cdna encoding luciferases from lampyris turkestanicus was transferred from pqe30 vector into pet28a expression vector and pltu28 was built. newly constructed vector was expressed in e. coli xl1 blue and the recombinant luc...

Nadir objective vector is constructed with the worst Pareto-optimal objective values in a multi-objective optimization problem and is an important entity to compute because of its importance in estimating the range of objective values in the Pareto-optimal front and also in using many interactive multi-objective optimization techniques. It is needed, for example, for normalizing purposes. The t...

in this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classifypatterns of different classes in the feature space. the introduced mutation operators and chaotic sequences allows us to overcomethe problem of early convergence into a local minima associated with particle swarm optimization algorithms. that is, the mutationope...

in this paper, a new alternative method for order reduction of high order systems is presented based on optimization of multi objective fitness function by using harmony search algorithm. at first, step response of full order system is obtained as a vector, then, a suitable fixed structure considered for model order reduction which order of original system is bigger than fixed structure model. ...

We introduce an unconstrained multicriteria optimization problem and discuss its relation to various well-known scalar robust optimization problems with a finite uncertainty set. Specifically, we show that a unique solution of a robust optimization problem is Pareto optimal for the unconstrained optimization problem. Furthermore, it is demonstrated that the set of weakly Pareto optimal solution...

We have obtained optimization methods to achieve minimum distortion levels for scalar and vector quantization. Unfortunately, the optimization methods are usually expensive and long. Many simpler methods to achieve (not as good as the optimal one, but) quite good performance have been developed both for scalar and for vector quantization applications. We will list a few of these many methods here.