Stochastic scheduling - A flow shop no wait application and solutions

Minimizing the makespan of a flow-shop no-wait (FSNW) schedule where the processing times are randomly distributed is an important NP-Complete Combinatorial Optimization Problem. In spite of this, it can be found only in very few papers in the literature. By considering the Start Interval Concept, this problem can be formulated, in a practical way, in function of the probability of the success in preserve FSNW constraints for all tasks execution. With this formulation, for the particular case with 3 machines, this paper presents different heuristics solutions: by integrating local optimization steps with insertion procedures and by using genetic algorithms for search the solution space. Computational results and performance evaluations are commented. Copyright (C) 1998 IFAC.

Modelo estocástico para dados GNSS e séries temporais de coordenadas GNSS

Pós-graduação em Ciências Cartográficas - FCT

Contextualização deposicional da formação Rio Claro no município de Paulínia/SP empregando simulações estocásticas

The Rio Claro Formation, Tertiary-Quaternary age, is composed of unconsolidated sediments deposited by fluvial systems. In Paulínia (SP) region geological studies comprising sedimentological, structural and geomorphological aspects indicate that the Rio Claro Formation is constituted by deposits of a meandering fluvial system. Data from SPT drillings were used to obtain sedimentary textural information in order to generate stochastic stratigraphic models. Particle size analysis was carried with the core samples which resulted in the distinction of five litofacies, three of which can be grouped into only one mudstone unit. The other two facies represent channel belt facies, being clayey sands and medium to coarse sands. Geostatistical modeling of the stratigraphic architecture followed together with correlation of analogue outcrop data and conceptual models for this type of depositional system. 100 models were generated with the SPT drillings and 50 models were generated with data from an analogue outcrop, which allowed constraining of both simulation sets to the depositional model given for the region. T-PROGS methodology has good applicability in simulating stratigraphic frameworks and its inherent limitations may be approached with parallel studies, such as stochastic modeling of analogue outcrops or geophysical methods

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

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

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modifying the stochastic model to mitigate GPS systematic errors in relative positioning

The GPS observables are subject to several errors. Among them, the systematic ones have great impact, because they degrade the accuracy of the accomplished positioning. These errors are those related, mainly, to GPS satellites orbits, multipath and atmospheric effects. Lately, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique (PLS). In this method, the errors are modeled as functions varying smoothly in time. It is like to change the stochastic model, in which the errors functions are incorporated, the results obtained are similar to those in which the functional model is changed. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method (CLS). In general, the solution requires a shorter data interval, minimizing costs. The method performance was analyzed in two experiments, using data from single frequency receivers. The first one was accomplished with a short baseline, where the main error was the multipath. In the second experiment, a baseline of 102 km was used. In this case, the predominant errors were due to the ionosphere and troposphere refraction. In the first experiment, using 5 minutes of data collection, the largest coordinates discrepancies in relation to the ground truth reached 1.6 cm and 3.3 cm in h coordinate for PLS and the CLS, respectively, in the second one, also using 5 minutes of data, the discrepancies were 27 cm in h for the PLS and 175 cm in h for the CLS. In these tests, it was also possible to verify a considerable improvement in the ambiguities resolution using the PLS in relation to the CLS, with a reduced data collection time interval. © Springer-Verlag Berlin Heidelberg 2007.

Basic ingredients for mathematical modeling of tumor growth in vitro: Cooperative effects and search for space

Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.

A Multi-Stage Stochastic Non-Linear Model for Reactive Power Planning Under Contingencies

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

Modeling amino acid requirements of poultry

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