Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.

Patogenicidade de Meloidogyne mayaguensis em goiabeira 'Paluma' em condições de microparcelas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Plantas antagonistas no manejo de Meloidogyne incognita, em solo arenoso de área de cultivo de olerícolas

The aim of this study was to evaluate the efficiency of antagonistic plants on nematode control in vegetables growing areas. The experiment was conducted in two periods in randomized complete block design in plots 1.5 x 1.4 m, corresponding to experimental units and randomly cultivated with the different plants. From each plot 100 cm(3) of soil and 10 g of tomato root were collected for estimating the initial population of the first and second experiment, respectively. Sixteen antagonistic plant seedlings of velvet bean (Stizolobium aterrimum), sunn plant (Crotalaria spectabilis) and pigeon pea (Cajanus cajan) were transferred to the plots and tomato (Solanun lycopersicum) cultivar Santa Clara was used as a control. After 116 days, two root systems and 100 cm(3) of soil were collected from each plot for a final nematode population analysis. Lettuce seedlings (Lactuca sativa) were transferred to the plots and evaluated after 28 and 42 days, respectively, for galls and eggs on the root system and fresh and dry weight of shoots,. Each treatment consisted of 6 replicates and the means were compared by LSD test (p<0.05). Meloidogyne incognita was found in the first survey. After the crop of the antagonistic plants, the M. incognita population in the root systems and the final population (soil + root) were statistically lower than in the control, which demonstrates the antagonistic effect of these plants on the nematode population. There were also a reduced number of galls on the lettuce cultivated after the antagonistic plants when compared to the control. The velvet bean and sunn plant showed an increase in dry shoot weight of the lettuce cultivated after the antagonists, respectively, in the first and second experiments.

Transmission system expansion planning by an extended genetic algorithm

The paper presents an extended genetic algorithm for solving the optimal transmission network expansion planning problem. Two main improvements have been introduced in the genetic algorithm: (a) initial population obtained by conventional optimisation based methods; (b) mutation approach inspired in the simulated annealing technique, the proposed method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Excellent performance is reported in the test results section of the paper for a difficult large-scale real-life problem: a substantial reduction in investment costs has been obtained with regard to previous solutions obtained via conventional optimisation methods and simulated annealing algorithms; statistical comparison procedures have been employed in benchmarking different versions of the genetic algorithm and simulated annealing methods.

Multistage and coordinated planning of the expansion of transmission systems

In this paper, an efficient genetic algorithm (GA) is presented to solve the problem of multistage and coordinated transmission expansion planning. This is a mixed integer nonlinear programming problem, difficult for systems of medium and large size and high complexity. The GA presented has a set of specialized genetic operators and an efficient form of generation of the initial population that finds high quality suboptimal topologies for large size and high complexity systems. In these systems, multistage and coordinated planning present a lower investment than static planning. Tests results are shown in one medium complexity system and one large size high complexity system.

Algoritmos evolutivos dedicados à reconfiguração de redes radiais de distribuição sob demandas fixas e variáveis: estudo dos operadores genéticos e parâmetros de controle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Seleção recorrente para produtividade e qualidade de frutos em abobrinha braquítica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Reprodução de Meloidogyne spp. em porta-enxertos e híbridos de pepino

A enxertia é uma técnica alternativa frequentemente recomendada para a cultura do pepino em áreas infestadas com nematóides das galhas. O presente trabalho teve como objetivo determinar o fator de reprodução de Meloidogyne javanica e de Meloidogyne incognita raça 2 em seis porta-enxertos para pepino (abóbora 'Menina Brasileira', moranga 'Exposição', 'Shelper', 'Tetsukabuto', 'B8-A Tetsukabuto' e 'Excite Ikki') e quatro híbridos de pepino (Cucumis sativus) tipo japonês ('Yoshinari', 'Kouki', 'Taisho' e 'Tsuyataro'). Foram conduzidos dois experimentos em casa-de-vegetação, um com cada espécie do nematóide, sendo cada parcela constituída de uma planta mantida em vaso contendo 2 litros de solo autoclavado. Nove dias após transplante, cada planta foi inoculada com 5.000 ovos e juvenis de segundo estádio (população inicial - Pi) de M. javanica ou M. incognita raça 2. Tomateiros 'Rutgers' foram utilizados como padrão de viabilidade do inóculo, em ambos os experimentos. O delineamento experimental foi inteiramente casualizado com cinco repetições por tratamento. Sessenta dias após a inoculação, cada planta foi avaliada, quanto ao peso fresco da raiz, número total de nematóides presentes no solo e na raiz (população final - Pf), número de nematóides/g de raiz e fator de reprodução de ambas as espécies de Meloidogyne (FR=Pf/Pi). Todos os porta-enxertos e híbridos de pepino testados apresentaram fatores de reprodução superiores a um, proporcionando a multiplicação de M. javanica e de M. incognita raça 2, porém, os valores nos híbridos de pepino foram superiores aos dos porta-enxertos.

Excited state dynamics of the Ho3+ ions in holmium singly doped and holmium, praseodymium-codoped fluoride glasses

The deactivation of the two lowest excited states of Ho3+ was investigated in Ho3+ singly doped and Ho3+, Pr3+-codoped fluoride (ZBLAN) glasses. We establish that 0.1-0.3 mol % Pr3+ can efficiently deactivate the first excited (I-5(7)) state of Ho3+ while causing a small reduction of similar to 40% of the initial population of the second excited (I-5(6)) state. The net effect introduced by the Pr3+ ion deactivation of the Ho3+ ion is the fast recovery of the ground state of Ho3+. The Burshstein model parameters relevant to the Ho3+-> Pr3+ energy transfer processes were determined using a least squares fit to the measured luminescence decay. The energy transfer upconversion and cross relaxation parameters for 1948, 1151, and 532 nm excitations of singly Ho3+-doped ZBLAN were determined. Using the energy transfer rate parameters we determine from the measured luminescence, a rate equation model for 650 nm excitation of Ho3+-doped and Ho3+, Pr3+-doped ZBLAN glasses was developed. The rate equations were solved numerically and the population inversion between the I-5(6) and the I-5(7) excited states of Ho3+ was calculated to examine the beneficial effects on the gain associated with Pr3+ codoping. (c) 2007 American Institute of Physics.

Evaluation of a multiobjective performance index for distribution systems with distributed generation

Here a multiobjective performance index for distribution systems with distributed generation based on a steady-state analysis of the network is proposed. This index quantifies the distributed generation impact on total losses, voltage profile and short circuit currents, and will be used as objective function in an evolutionary algorithm aimed at searching the best points for connecting distributed generators. Moreover, a loss allocation technique, based on the Zbus method, is applied on the original configuration of the network to obtain a good quality initial population. An IEEE medium voltage distribution network is analysed and results are presented and discussed.

An enhanced genetic algorithm to solve the static and multistage transmission network expansion planning

An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1) generation of an initial population using fast, efficient heuristic algorithms, (2) better implementation of the local improvement phase and (3) efficient solution of linear programming problems (LPs). Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem. Copyright © 2012 Luis A. Gallego et al.

A genetic algorithm for crop rotation

In the last few years, crop rotation has gained attention due to its economic, environmental and social importance which explains why it can be highly beneficial for farmers. This paper presents a mathematical model for the Crop Rotation Problem (CRP) that was adapted from literature for this highly complex combinatorial problem. The CRP is devised to find a vegetable planting program that takes into account green fertilization restrictions, the set-aside period, planting restrictions for neighboring lots and for crop sequencing, demand constraints, while, at the same time, maximizing the profitability of the planted area. The main aim of this study is to develop a genetic algorithm and test it in a real context. The genetic algorithm involves a constructive heuristic to build the initial population and the operators of crossover, mutation, migration and elitism. The computational experiment was performed for a medium dimension real planting area with 16 lots, considering 29 crops of 10 different botanical families and a two-year planting rotation. Results showed that the algorithm determined feasible solutions in a reasonable computational time, thus proving its efficacy for dealing with this practical application.

Vigor de sementes, população de plantas e desempenho agrônomico de soja

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Intensificação do cultivo de Macrobrachium amazonicum: efeito das estratégias de estocagem e despesca na água dos viveiros, efluentes e sedimentação em viveiros de crescimento final

Pós-graduação em Aquicultura - FCAV

Avaliação de operadores de algoritmos genéticos em otimização multidimensional

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)