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Stochastic algorithms in discrete optimization with noisy values for the function

100%

Wieczorkowski R.

Mathematica Applicanda

1995

tom 24

nr 38

The paper deals with stochastic methods for searching approximately global minimum of function defined on discrete set. A measure of quality of solution is defined to compare different algorithms. Simple Monte Carlo method is analysed as main algorithm for which formulas dealing with the measure of quality are derived(two cases: exact values and noisy values of function). This Monte Carlo method is used as a base in simulation experiments for comparing other stochastic algorithms. The second part of the paper analyses asymptotic properties of the generalised simulated annealing algorithms. Theory of Markov chains is used in modelling this class of algorithms. Theorems about convergence of the records of algorithms to set of optima with probability one are presented in the case of function having random noisy values. The paper also reviews known results in the field of simulated annealing type algorithms for function with randomly perturbated values.

Some properties and applications of a distribution-free quantile estimator

63%

Wieczorkowski R., Zieliński R.

Mathematica Applicanda

1991

tom 20

nr 34

In the paper Zielinski (1988) a distribution-free median-unbiased quantile estimator was proposed. We study some properties, asymptotic properties among them, of that estimator, and we discuss its usefulness as a robust estimator of a quantile in maximally violated exponential distribution.

Ograniczanie wyników

2 Mathematica Applicanda

2 Wieczorkowski R.

1 Zieliński R.

1 1995

1 1991

Wyniki wyszukiwania

Stochastic algorithms in discrete optimization with noisy values for the function

Some properties and applications of a distribution-free quantile estimator