An optimization approach applied to the optimal stratification problem

A new optimization algorithm is presented to solve the stratification problem. Assuming the number L of strata and the total sample size n are fixed, we obtain strata boundaries by using an objective function associated with the variance. In this problem, strata boundaries must be determined so that the elements in each stratum are more homogeneous among themselves. To produce more homogeneous strata, this paper proposes a new algorithm that uses the Greedy Randomized Adaptive Search Procedure (GRASP) methodology. Computational results are presented for a set of problems, with the application of the new algorithm and some algorithms from literature.     

Native and exotic species in the urban landscape of the city of Rio de Janeiro,Brazil: density,richness, and arboreal deficit

Shaped by European influences, the Brazilian urban landscape was marked by the predominant use of exotic species in planted areas. In the 19th century along the city streets of Rio de Janeiro, trees were planted at a standard distance from each other. With time, native species began to be used in the urban landscape. Our purpose was to evaluate the utilization of exotic plant species in the urban landscape of Rio de Janeiro, evaluate the city’s arboreal deficit, and relate its neighborhood arboreal density to its economic index. Arboreal deficit represents the negative difference between the total number of expected trees and the observed number in the streets based in the standard distance used in the past. Twenty native and 40 exotic species were found in the 1701 streets sampled. A high percent of streets did not have any planted trees and the number of trees was greater in wealthier neighborhoods. The strong prevalence of exotic species is indicative of the negative impact of human activity on the biota. Since the municipality of Rio de Janeiro harbors forested areas, the risk for dissemination of exotic species is high.     

Social and academic profile of the university student of social work a comparative study in Spain,Argentina, and Venezuela

ABSTRACT

The article presents the results of an empirical investigation that aimed to analyze comparative socio-demographic characteristics, motivational aspects and professional role of students who attend universities. The contexts of research were University of Mar de Plata (Argentina), University of Murcia (Spain) and University of Zulia (Venezuela). The universe of research was 304 students, with the participation of a total of 253 (TR 83,2%), 109 from University of Murcia—Spain—100 from University of Mar del Plata—Argentina and 44 from University of Zulia—Venezuela. Two hundred and forty-four measuring instruments were checked favorably. The results of the research allowed to highlight significant coincidences in most of the variables studied. In the analysis of self-perceived personality styles, there is high coincidence both in style (attributed qualification) and score (assigned quantification). At the three universities, the docent–student relationship is a positive variable that affects the favorable self-perception beyond academic success. Design and implementation of programs based on the described characteristics are recommended.     

A hybrid biased random key genetic algorithm approach for the unit commitment problem

This work proposes a hybrid genetic algorithm (GA) to address the unit commitment (UC) problem. In the UC problem, the goal is to schedule a subset of a given group of electrical power generating units and also to determine their production output in order to meet energy demands at minimum cost. In addition, the solution must satisfy a set of technological and operational constraints. The algorithm developed is a hybrid biased random key genetic algorithm (HBRKGA). It uses random keys to encode the solutions and introduces bias both in the parent selection procedure and in the crossover strategy. To intensify the search close to good solutions, the GA is hybridized with local search. Tests have been performed on benchmark large-scale power systems. The computational results demonstrate that the HBRKGA is effective and efficient. In addition, it is also shown that it improves the solutions obtained by current state-of-the-art methodologies.