Distribuição diária do comportamento da mosca da fruta Anastrepha zenildae Zucchi, (Diptera: Tephritidae) em laboratório.

The knowledge of Anastrepha zenildae behavioral aspects combined with the biology of Tephritidae may contribute to monitoring and control programs of this fruit fly that is considered as economically important to the Rio Grande do Norte state. In order to characterize the daily activity profile of this species, we studied the behaviors of resting, locomotion, feeding, cleaning, courtship, copulation and oviposition of animals submitted to an artificial 12:12h light-dark cycle (750:1lux) with controlled temperature (26±2 °C). The observations were made with groups of 16 males and 16 females during 3 consecutive days each generation from parental to F5. Resting, locomotion, feeding and cleaning data were recorded as frequency and time of occurrence by scanning technique in 15 minutes windows per hour, with a record each minute. Courtship, copulation and oviposition were recorded as frequency, time of occurrence and duration by al occurrences technique. Resting was the most frequent behavior with males resting more than females. Locomotion was more evident in the first half of the ligh phase with higher values in females. Cleaning and feeding behaviors were more frequent in the second half of the light phase for both sexes with females eating more frequently than males. During the courtship, males were grouped in lek formations showing wings vibration and pheromone liberation. Courtship occurred more frequently 4 to 7 h after lights on (81,9%) with copulations being more frequent 6 h after lights on with a mean duration of 58,1±40,4 min. Copulation attempts were observed in males inside and outside the lek with aggressive behavior being observed only between males in the lek. Oviposition behavior was similar to that described for other species of the genus with a peak of this activity 2-3 h after the lights on, mean duration of 43, 7±34, 8 sec and 2 to 5 eggs by event. According to the results, sexual behavior of A. zenildae is temporally different of other sympatric species of the genus, being favorable to the reproductive isolation as well as the use of resources as oviposition substrate.

O problema do caixeiro viajante alugador : um estudo algorítmico

The Car Rental Salesman Problem (CaRS) is a variant of the classical Traveling Salesman Problem which was not described in the literature where a tour of visits can be decomposed into contiguous paths that may be performed in different rental cars. The aim is to determine the Hamiltonian cycle that results in a final minimum cost, considering the cost of the route added to the cost of an expected penalty paid for each exchange of vehicles on the route. This penalty is due to the return of the car dropped to the base. This paper introduces the general problem and illustrates some examples, also featuring some of its associated variants. An overview of the complexity of this combinatorial problem is also outlined, to justify their classification in the NPhard class. A database of instances for the problem is presented, describing the methodology of its constitution. The presented problem is also the subject of a study based on experimental algorithmic implementation of six metaheuristic solutions, representing adaptations of the best of state-of-the-art heuristic programming. New neighborhoods, construction procedures, search operators, evolutionary agents, cooperation by multi-pheromone are created for this problem. Furtermore, computational experiments and comparative performance tests are conducted on a sample of 60 instances of the created database, aiming to offer a algorithm with an efficient solution for this problem. These results will illustrate the best performance reached by the transgenetic algorithm in all instances of the dataset

Uma colônia de formigas para o caminho mais curto multiobjetivo

Multi-objective combinatorial optimization problems have peculiar characteristics that require optimization methods to adapt for this context. Since many of these problems are NP-Hard, the use of metaheuristics has grown over the last years. Particularly, many different approaches using Ant Colony Optimization (ACO) have been proposed. In this work, an ACO is proposed for the Multi-objective Shortest Path Problem, and is compared to two other optimizers found in the literature. A set of 18 instances from two distinct types of graphs are used, as well as a specific multiobjective performance assessment methodology. Initial experiments showed that the proposed algorithm is able to generate better approximation sets than the other optimizers for all instances. In the second part of this work, an experimental analysis is conducted, using several different multiobjective ACO proposals recently published and the same instances used in the first part. Results show each type of instance benefits a particular type of instance benefits a particular algorithmic approach. A new metaphor for the development of multiobjective ACOs is, then, proposed. Usually, ants share the same characteristics and only few works address multi-species approaches. This works proposes an approach where multi-species ants compete for food resources. Each specie has its own search strategy and different species do not access pheromone information of each other. As in nature, the successful ant populations are allowed to grow, whereas unsuccessful ones shrink. The approach introduced here shows to be able to inherit the behavior of strategies that are successful for different types of problems. Results of computational experiments are reported and show that the proposed approach is able to produce significantly better approximation sets than other methods