Random key genetic algorithms are heuristic methods for solving combinatorial optimization problems. They represent solutions as vectors of randomly generated real numbers, the so-called random keys. A deterministic algorithm, called a decoder, takes as input a vector of random keys and associates with it a feasible solution of the combinatorial optimization problem for which an objective value or fitness can be computed. We compare three types of random-key genetic algorithms: the unbiased algorithm of Bean (1994); the biased algorithm of Gonçalves and Resende (2010); and a greedy version of Bean's algorithm on 12 instances from four types of covering problems: general-cost set covering, Steiner triple covering, general-cost set k -covering, and unit-cost covering by pairs. Experiments are run to construct runtime distributions for 36 heuristic/instance pairs. For all pairs of heuristics, we compute probabilities that one heuristic is faster than the other on all 12 instances. The experiments show that, in 11 of the 12 instances, the greedy version of Bean's algorithm is faster than Bean's original method and that the biased variant is faster than both variants of Bean's algorithm.

The freshwater phase of Atlantic salmon Salmo salar L vary between one and eight years. The reduction of the freshwater phase is desirable to reduce freshwater usage, human resources and to increase year round availability of pan-sized salmon. Three trials were conducted to investigate the possibility of supply the market in a year-round basis, with pan-sized Atlantic salmon Salmo salar L. (250-300 g) in Portugal (southern limit of the natural distribution of this species). This study primarily aimed to compare the osmoregulatory ability and growth of different fish sizes, smolts 1+ (trial 1), 1.5+ (trial 2) and 2+ (trial 3), in freshwater and seawater conditions. Additionally, effects of photoperiod were determined in smolts 1.5+ (trial 2) for both freshwater and seawater groups. The increments in the plasma osmolality and chlorine concentrations after seawater transfer suggest an identical development in the hypo-osmoregulation capacity among the different age classes. In all trials, weight gain was smaller after 30 d of saltwater transfer when compared to fish reared in freshwater. However, the growth depression was temporary. Seawater group showed a compensatory growth in the immediate months, which permitted an improvement in growth rates. At the end of trials there were minor differences on growth performance between freshwater and seawater groups. Specific growth rates varied between 0.7 and 1.0 % day-1, according to the age and /or size and transfer season.

A aquicultura de pregado (Scophthalmus maximus) utilizando elevadas densidades pode reduzir o crescimento e aumentar os custos de produção. Elevados níveis de metabolitos gerados nestes sistemas intensivos provocam rápida deterioração da qualidade da água, podendo também comprometer a performance da produção. A L-carnitina atua como potenciadora do crescimento parecendo ser promissora por atenuar alguns desses efeitos. Os efeitos de densidades (4, 8, 11 e 14 kg m²) no desempenho do crescimento, composição corporal foram avaliados em pregados (75,6 ± 2,8 g) alimentados durante 75 dias a dois níveis dietéticos de L-carnitina (40 ou 240 mg kg¹). Após esse período, determinou-se a excreção de amônia pós-prandial durante 24 horas. Os peixes cultivados na menor densidade, 4 kg m², apresentaram melhores taxas de crescimento e ganho de peso (94-96 g) em comparação aos mantidos em altas densidades (80-87 g). A taxa de eficiência proteica foi mais elevada a 4 kg m² (1,33-1,36), do que a densidades de 8 kg m² (0,98) ou 14 kg m² (0,45). A ingestão voluntária de alimento decresceu de 0,70 para 0,56% do peso corporal com o incremento da densidade. A suplementação de carnitina não afetou o crescimento e a composição corporal, com exceção do conteúdo de carnitine da carcaça que passou de 75 a 128 mg kg¹. Peixes alimentados com suplementos de 240 mg L-carnitina apresentam excreção de amônia mais baixa comparativamente aos alimentados com 40 mg L-carnitina (p < 0,05).

Commercial farming of turbot (Scophthalmus maximus) at high stocking densities may lead to growth depression and increasing production costs. Moreover, the high levels of accumulated waste in an intensive system may cause rapid deterioration of water quality, which may undermine the production. L-carnitine is known as a growth-enhancer which shows promise as mitigator of crowding effects. The effects of stocking densities (4, 8, 11 and 14 kg m²) on growth performance, feed utilization and body composition were evaluated during 75 days on turbot (75.6 ± 2.8 g) fed two dietary L-carnitine levels (40 or 240 mg kg¹). At the end of the feeding trial, total ammonia excretion (TAN) was measured postprandially for 24h. Specific growth rate and weight gain decreased with increasing stocking density. Fish held at 4 kg m² had higher final body weight (94-96 g) than fish held at higher densities (80-87 g). Protein efficiency ratio was higher in fish held at 4 kg m² (1.33-1.36), in comparison to fish stocked at 8 kg m² (0.98) or 14 kg m² (0.45). Voluntary feed intake decreased from 0.70 to 0.56% BW with increasing stocking density. Dietary L-carnitine supplementation did not affect growth performance and body composition, except for body L-carnitine content which increased from 75 to 128 mg kg¹ BW with supplementation. Fish fed 240 mg L-carnitine supplements had lower TAN that the ones fed 40 mg L-carnitine (p < 0.05).

Neste artigo apresenta-se um algoritmo genético para o Problema do Sequenciamento de Projectos com Recursos Limitados (RCPSP). A representação cromossómica utilizada baseia-se em chaves aleatórias. O sequenciamento das actividades é feito com recurso a uma heurística baseada em prioridades definidas pelo algoritmo genético. A heurística gera sequenciamentos activos parametrizados. O algoritmo é testado num conjunto de problemas padrão retirados da literatura da especialidade e é comparado com outras abordagens. Os resultados computacionais validam o bom desempenho do algoritmo em termos de qualidade da solução.

This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach is tested on a set of standard problems taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.