145 resultados para Availability Heuristic

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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This paper addresses the capacitated lot sizing problem (CLSP) with a single stage composed of multiple plants, items and periods with setup carry-over among the periods. The CLSP is well studied and many heuristics have been proposed to solve it. Nevertheless, few researches explored the multi-plant capacitated lot sizing problem (MPCLSP), which means that few solution methods were proposed to solve it. Furthermore, to our knowledge, no study of the MPCLSP with setup carry-over was found in the literature. This paper presents a mathematical model and a GRASP (Greedy Randomized Adaptive Search Procedure) with path relinking to the MPCLSP with setup carry-over. This solution method is an extension and adaptation of a previously adopted methodology without the setup carry-over. Computational tests showed that the improvement of the setup carry-over is significant in terms of the solution value with a low increase in computational time.

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This study aims to estimate an adult-equivalent scale for calorie requirements and to determine the differences between adult-equivalent and per capita measurements of calorie availability in the Brazilian population. The study used data from the 2002-2003 Brazilian Household Budget Survey. The calorie requirement for a reference adult individual was based on the mean requirements for adult males and females (2,550kcal/day). The conversion factors were defined as the ratios between the calorie requirements for each age group and gender and that of the reference adult. The adult-equivalent calorie availability levels were higher than the per capita levels, with the largest differences in rural and low-income households. Differences in household calorie availability varied from 22kcal/day (households with adults and an adolescent) to 428kcal/day (households with elderly individuals), thus showing that per capital measurements can underestimate the real calorie availability, since they overlook differences in household composition.

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Background: Bayesian mixing models have allowed for the inclusion of uncertainty and prior information in the analysis of trophic interactions using stable isotopes. Formulating prior distributions is relatively straightforward when incorporating dietary data. However, the use of data that are related, but not directly proportional, to diet (such as prey availability data) is often problematic because such information is not necessarily predictive of diet, and the information required to build a reliable prior distribution for all prey species is often unavailable. Omitting prey availability data impacts the estimation of a predator's diet and introduces the strong assumption of consumer ultrageneralism (where all prey are consumed in equal proportions), particularly when multiple prey have similar isotope values. Methodology: We develop a procedure to incorporate prey availability data into Bayesian mixing models conditional on the similarity of isotope values between two prey. If a pair of prey have similar isotope values (resulting in highly uncertain mixing model results), our model increases the weight of availability data in estimating the contribution of prey to a predator's diet. We test the utility of this method in an intertidal community against independently measured feeding rates. Conclusions: Our results indicate that our weighting procedure increases the accuracy by which consumer diets can be inferred in situations where multiple prey have similar isotope values. This suggests that the exchange of formalism for predictive power is merited, particularly when the relationship between prey availability and a predator's diet cannot be assumed for all species in a system.

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We investigate the performance of a variant of Axelrod's model for dissemination of culture-the Adaptive Culture Heuristic (ACH)-on solving an NP-Complete optimization problem, namely, the classification of binary input patterns of size F by a Boolean Binary Perceptron. In this heuristic, N agents, characterized by binary strings of length F which represent possible solutions to the optimization problem, are fixed at the sites of a square lattice and interact with their nearest neighbors only. The interactions are such that the agents' strings (or cultures) become more similar to the low-cost strings of their neighbors resulting in the dissemination of these strings across the lattice. Eventually the dynamics freezes into a homogeneous absorbing configuration in which all agents exhibit identical solutions to the optimization problem. We find through extensive simulations that the probability of finding the optimal solution is a function of the reduced variable F/N(1/4) so that the number of agents must increase with the fourth power of the problem size, N proportional to F(4), to guarantee a fixed probability of success. In this case, we find that the relaxation time to reach an absorbing configuration scales with F(6) which can be interpreted as the overall computational cost of the ACH to find an optimal set of weights for a Boolean binary perceptron, given a fixed probability of success.

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Addressing spatial variability in nitrogen (N) availability in the Central Brazilian Amazon, we hypothesized that N availability varies among white-sand vegetation types (campina and campinarana) and lowland tropical forests (dense terra-firme forests) in the Central Brazilian Amazon, under the same climate conditions. Accordingly, we measured soil and foliar N concentration and N isotope ratios (delta(15)N) throughout the campina-campinarana transect and compared to published dense terra-firme forest results. There were no differences between white-sand vegetation types in regard to soil N concentration, C:N ratio and delta(15)N across the transect. Both white-sand vegetation types showed very low foliar N concentrations and elevated foliar C:N ratios, and no significant difference between site types was observed. Foliar delta(15)N was depleted, varying from -9.6 to 1.6aEuro degrees in the white-sand vegetations. The legume Aldina heterophylla had the highest average delta(15)N values (-1.5aEuro degrees) as well as the highest foliar N concentration (2.1%) while the non-legume species had more depleted delta(15)N values and the average foliar N concentrations varied from 0.9 to 1.5% among them. Despite the high variation in foliar delta(15)N among plants, a significant and gradual (15)N-enrichment in foliar isotopic signatures throughout the campina-campinarana transect was observed. Individual plants growing in the campinarana were significantly enriched in (15)N compared to those in campina. In the white-sand N-limited ecosystems, the differentiation of N use seems to be a major cause of variations observed in foliar delta(15)N values throughout the campina-campinarana transect.

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Nitrogen variations at different spatial scales and integrated across functional groups were addressed for lowland tropical forests in the Brazilian Amazon as follows: (1) how does N availability vary across the region over different spatial scales (regional x landscape scale); ( 2) how are these variations in N availability integrated across plant functional groups ( legume 9 non-legume trees). Leaf N, P, and Ca concentrations as well the leaf N isotope ratios (delta(15)N) from a large set of legume and non-legume tree species were measured. Legumes had higher foliar N/Ca ratios than non-legumes, consistent with the high energetic costs in plant growth associated with higher foliar P/Ca ratios found in legumes than in non-legumes. At the regional level, foliar delta(15)N decreased with increasing rainfall. At the landscape level, N availability was higher in the forests on clayey soils on the plateau than in forests on sandier soils. The isotope as well as the non-isotope data relationships here documented, explain to a large extent the variation in delta(15)N signatures across gradients of rainfall and soil. Although at the regional level, the precipitation regime is a major determinant of differences in N availability, at the landscape level, under the same precipitation regime, soil type seems to be a major factor influencing the availability of N in the Brazilian Amazon forest.

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The paper discusses the availability of biomass in Brazil to supply charcoal to the steel industry on the bases of an initial global assessment of land potentially available for plantations and of Brazilian data that allows refining the assessment and specifying the issue of practical availability. Technical potentials are first assessed through a series of simple rules against direct competition with agriculture, forests and protected areas, and of quantitative criteria, whether geo-climatic (rainfall), demographic (population density) or legal (reserves). Institutional, social and economic factors are then identified and discussed so as to account for the practical availability of Brazilian biomass through six criteria. The ranking of nine Brazilian States according to these criteria brings out the necessary trade-offs in the selection of land for plantations that would efficiently supply charcoal to the steel industry. (C) 2008 Elsevier Ltd. All rights reserved.

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Aims: The main objective of this study was to evaluate the behaviour of the brown-rot fungus Wolfiporia cocos under differential iron availability. Methods and Results: W. cocos was grown under three differential iron conditions. Growth, catecholate and hydroxamate production, and mycelial and extracellular Fe3+-reducing activities were determined. Iron starvation slowed fungal growth and accelerated pH decline. Some mycelial proteins of low molecular weight were repressed under iron restriction, whereas others of high molecular weight showed positive iron regulation. Mycelial ferrireductase activity decreased as culture aged, while Fe3+-reducing activity of low molecular reductants constantly increased. Hydroxamates production suffered only limited iron repression, whereas catecholates production showed to be more iron repressible. Conclusions: W. cocos seems to possess more than one type of iron acquisition mechanism; one involving secretion of organic acids and ferrireductases and/or extracellular reductants, and another relying on secretion of catecholates and hydroxamates chelators. Significance and Impact of the Study: This paper is the first to report the kinetic study of brown-rot fungus grown under differential iron availability, and the information provided here contributes to address more traditional problems in protecting wood from brown decay, and also makes a contribution in the general area of the physiology of brown-rot fungi.

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A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (C) 2010 Elsevier B.V. All rights reserved.

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In this paper, we address the problem of scheduling jobs in a no-wait flowshop with the objective of minimising the total completion time. This problem is well-known for being nondeterministic polynomial-time hard, and therefore, most contributions to the topic focus on developing algorithms able to obtain good approximate solutions for the problem in a short CPU time. More specifically, there are various constructive heuristics available for the problem [such as the ones by Rajendran and Chaudhuri (Nav Res Logist 37: 695-705, 1990); Bertolissi (J Mater Process Technol 107: 459-465, 2000), Aldowaisan and Allahverdi (Omega 32: 345-352, 2004) and the Chins heuristic by Fink and Voa (Eur J Operat Res 151: 400-414, 2003)], as well as a successful local search procedure (Pilot-1-Chins). We propose a new constructive heuristic based on an analogy with the two-machine problem in order to select the candidate to be appended in the partial schedule. The myopic behaviour of the heuristic is tempered by exploring the neighbourhood of the so-obtained partial schedules. The computational results indicate that the proposed heuristic outperforms existing ones in terms of quality of the solution obtained and equals the performance of the time-consuming Pilot-1-Chins.

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Limited information is available on the interactions between environmental factors and algal growth in tropical and subtropical aquatic systems. We investigated the relationships between algal biomass (measured as chlorophyll, Chl-a) and light, total phosphorus (TP) and total nitrogen (TN) in longitudinal zones of subtropical reservoirs. We studied the seasonal variation of water variables in Itupararanga Reservoir (Brazil) and compared the results with 16 other subtropical lakes and reservoirs. The longitudinal zones in Itupararanga Reservoir were considered statistically different (p 0.05, MANOVA). From the riverine zone to the dam region of the reservoir, Spearman Correlation Test suggested that light limitation and TP limitation tended to decrease and increase, respectively. Although nitrate concentrations were high (400 g/L), the Spearman coefficients between Chl-a and TN and the TN:TP ratios (11:1 TN:TP 35:1) indicated that nitrogen may be co-limiting algal growth in the studied water body. Putting Itupararanga in a regional context allowed assessment of potential influences of land use on trophic state. Within the subtropical dataset, TP explained a greater percentage of variance in Chl-a (R2 = 0.70) than TN (R2 = 0.17). The main land use type within the reservoirs drainage area significantly influenced the concentrations of TP, TN, and Chl-a (p 0.05, MANOVA), with different relationships between nutrients and chlorophyll in forested (R2 = 0.12-0.33), agricultural (R2 = 0.50-0.68) and urban (R2 = 0.09-0.64) watersheds. Comparisons with literature values and those from reservoirs with less altered watersheds indicated that Itupararanga Reservoir is reaching the mesotrophic-eutrophic boundary, and further nutrient enrichment could cause water quality degradation.

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This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

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The combined-cycle gas and steam turbine power plant presents three main pieces of equipment: gas turbines, steam turbines and heat recovery steam generator (HRSG). In case of HRSG failure the steam cycle is shut down, reducing the power plant output. Considering that the technology for design, construction and operation of high capacity HRSGs is quite recent its availability should be carefully evaluated in order to foresee the performance of the power plant. This study presents a method for reliability and availability evaluation of HRSGs installed in combined-cycle power plant. The method`s first step consists in the elaboration of the steam generator functional tree and development of failure mode and effects analysis. The next step involves a reliability and availability analysis based on the time to failure and time to repair data recorded during the steam generator operation. The third step, aiming at availability improvement, recommends the fault-tree analysis development to identify components the failure (or combination of failures) of which can cause the HRSG shutdown. Those components maintenance policy can be improved through the use of reliability centered maintenance (RCM) concepts. The method is applied on the analysis of two HRSGs installed in a 500 MW combined-cycle power plant. (C) 2010 Elsevier Ltd. All rights reserved.

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This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization (PSO), and 1-opt local search (1-LS) heuristic multiuser detection algorithms (Heur-MuDs) are analyzed in details, using a single-objective antenna-diversity-aided optimization approach. Monte- Carlo simulations show that, after convergence, the performances reached by all near-optimum Heur-MuDs are similar. However, the computational complexities may differ substantially, depending on the system operation conditions. Their complexities are carefully analyzed in order to obtain a general complexity-performance framework comparison and to show that unitary Hamming distance search MuD (uH-ds) approaches (1-LS, SA, RTS and STTS) reach the best convergence rates, and among them, the 1-LS-MuD provides the best trade-off between implementation complexity and bit error rate (BER) performance.

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This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.