Abstract. In this paper we consider some four-parametric, so-called Generalized Pareto-like Frequency Distribution, which have been constructed using stochastic Birth-Death Process in order to model phenomena arising in Bioinformatics (Astola and Danielian, 2007). As examples, two ”real data” sets on the number of proteins and number of residues for analyzing such distribution are given. The co...

Decomposition-based algorithms for multi-objective optimization problems have increased in popularity in the past decade. Although their convergence to the Pareto optimal front (PF) is in several instances superior to that of Pareto-based algorithms, the problem of selecting a way to distribute or guide these solutions in a high-dimensional space has not been explored. In this work, we introduc...

Motivated by a practical application, this paper investigates robust estimation of economic indicators from survey samples based on a semiparametric Pareto tail model. Economic performance is typically measured by a set of indicators, which are often estimated from survey data – the motivating example being the European indicators on social exclusion and poverty computed from the well known EU-...

A genetic algorithm for multiobjective optimization is presented which tries to evolve an evenly distributed set of solutions belonging to the Pareto set by: (i) ranking the population according to nondomination properties; (ii) defining a filter to retain Pareto set solutions and (iii) using adequate operators: exclusion, addition and single-objective operator which improves the individuals fr...

A packet transmission delay is an important quality characteristic for various applications including real-time and data applications. In particular, it is necessary to investigate not only a whole distribution of the packet transmission delay, but also the tail part of the distribution, in order to detect the packet loss. In this paper, we analyze the characteristics of the tail part of packet...

• We propose an estimator of the Pareto tail index m of a distribution, that competes well with the Hill, Pickands and moment estimators. Unlike the above estimators, that are based only on the extreme observations, the proposed estimator uses all observations; its idea rests in the tail behavior of the sample mean X̄n, having a simple structure under heavy-tailed F . The observations, partition...

The optimization of multiple conflictive objectives at the same time is a hard problem. In most cases, a uniform distribution of solutions on the Pareto front is the main objective. We propose a novel evolutionary multi-objective algorithm that is based on the selection with regard to equidistant lines in the objective space. The so-called rakes can be computed efficiently in high dimensional o...