A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Improving node number simulation in soybean

The objective of this study was to improve the simulation of node number in soybean cultivars with determinate stem habits. A nonlinear model considering two approaches to input daily air temperature data (daily mean temperature and daily minimum/maximum air temperatures) was used. The node number on the main stem data of ten soybean cultivars was collected in a three-year field experiment (from 2004/2005 to 2006/2007) at Santa Maria, RS, Brazil. Node number was simulated using the Soydev model, which has a nonlinear temperature response function [f(T)]. The f(T) was calculated using two methods: using daily mean air temperature calculated as the arithmetic average among daily minimum and maximum air temperatures (Soydev tmean); and calculating an f(T) using minimum air temperature and other using maximum air temperature and then averaging the two f(T)s (Soydev tmm). Root mean square error (RMSE) and deviations (simulated minus observed) were used as statistics to evaluate the performance of the two versions of Soydev. Simulations of node number in soybean were better with the Soydev tmm version, with a 0.5 to 1.4 node RMSE. Node number can be simulated for several soybean cultivars using only one set of model coefficients, with a 0.8 to 2.4 node RMSE.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Brittle to ductile transition in a fiber bundle with strong heterogeneity

We analyze the failure process of a two-component system with widely different fracture strength in the framework of a fiber bundle model with localized load sharing. A fraction 0≤α≤1 of the bundle is strong and it is represented by unbreakable fibers, while fibers of the weak component have randomly distributed failure strength. Computer simulations revealed that there exists a critical composition αc which separates two qualitatively different behaviors: Below the critical point, the failure of the bundle is brittle, characterized by an abrupt damage growth within the breakable part of the system. Above αc, however, the macroscopic response becomes ductile, providing stability during the entire breaking process. The transition occurs at an astonishingly low fraction of strong fibers which can have importance for applications. We show that in the ductile phase, the size distribution of breaking bursts has a power law functional form with an exponent μ=2 followed by an exponential cutoff. In the brittle phase, the power law also prevails but with a higher exponent μ=92. The transition between the two phases shows analogies to continuous phase transitions. Analyzing the microstructure of the damage, it was found that at the beginning of the fracture process cracks nucleate randomly, while later on growth and coalescence of cracks dominate, which give rise to power law distributed crack sizes.

Simulation of surface waves in porous media

We present a novel numerical algorithm for the simulation of seismic wave propagation in porous media, which is particularly suitable for the accurate modelling of surface wave-type phenomena. The differential equations of motion are based on Biot's theory of poro-elasticity and solved with a pseudospectral approach using Fourier and Chebyshev methods to compute the spatial derivatives along the horizontal and vertical directions, respectively. The time solver is a splitting algorithm that accounts for the stiffness of the differential equations. Due to the Chebyshev operator the grid spacing in the vertical direction is non-uniform and characterized by a denser spatial sampling in the vicinity of interfaces, which allows for a numerically stable and accurate evaluation of higher order surface wave modes. We stretch the grid in the vertical direction to increase the minimum grid spacing and reduce the computational cost. The free-surface boundary conditions are implemented with a characteristics approach, where the characteristic variables are evaluated at zero viscosity. The same procedure is used to model seismic wave propagation at the interface between a fluid and porous medium. In this case, each medium is represented by a different grid and the two grids are combined through a domain-decomposition method. This wavefield decomposition method accounts for the discontinuity of variables and is crucial for an accurate interface treatment. We simulate seismic wave propagation with open-pore and sealed-pore boundary conditions and verify the validity and accuracy of the algorithm by comparing the numerical simulations to analytical solutions based on zero viscosity obtained with the Cagniard-de Hoop method. Finally, we illustrate the suitability of our algorithm for more complex models of porous media involving viscous pore fluids and strongly heterogeneous distributions of the elastic and hydraulic material properties.

Feasibility of Visualization and Simulation Applications to Improve Work Zone Safety and Mobility

Visualization is a relatively recent tool available to engineers for enhancing transportation project design through improved communication, decision making, and stakeholder feedback. Current visualization techniques include image composites, video composites, 2D drawings, drive-through or fly-through animations, 3D rendering models, virtual reality, and 4D CAD. These methods are used mainly to communicate within the design and construction team and between the team and external stakeholders. Use of visualization improves understanding of design intent and project concepts and facilitates effective decision making. However, visualization tools are typically used for presentation only in large-scale urban projects. Visualization is not widely accepted due to a lack of demonstrated engineering benefits for typical agency projects, such as small- and medium-sized projects, rural projects, and projects where external stakeholder communication is not a major issue. Furthermore, there is a perceived high cost of investment of both financial and human capital in adopting visualization tools. The most advanced visualization technique of virtual reality has only been used in academic research settings, and 4D CAD has been used on a very limited basis for highly complicated specialty projects. However, there are a number of less intensive visualization methods available which may provide some benefit to many agency projects. In this paper, we present the results of a feasibility study examining the use of visualization and simulation applications for improving highway planning, design, construction, and safety and mobility.

Feasibility of Visualization and Simulation Applications, Tech Transfer Summary, 2008

Visualization is a relatively recent tool available to engineers for enhancing transportation project design through improved communication, decision making, and stakeholder feedback. Current visualization techniques include image composites, video composites, 2D drawings, drive-through or fly-through animations, 3D rendering models, virtual reality, and 4D CAD. These methods are used mainly to communicate within the design and construction team and between the team and external stakeholders. Use of visualization improves understanding of design intent and project concepts and facilitates effective decision making. However, visualization tools are typically used for presentation only in large-scale urban projects. Visualization is not widely accepted due to a lack of demonstrated engineering benefits for typical agency projects, such as small- and medium-sized projects, rural projects, and projects where external stakeholder communication is not a major issue. Furthermore, there is a perceived high cost of investment of both financial and human capital in adopting visualization tools. The most advanced visualization technique of virtual reality has only been used in academic research settings, and 4D CAD has been used on a very limited basis for highly complicated specialty projects. However, there are a number of less intensive visualization methods available which may provide some benefit to many agency projects. In this paper, we present the results of a feasibility study examining the use of visualization and simulation applications for improving highway planning, design, construction, and safety and mobility.

Work Zone Simulation Model, 1999

To support the analysis of driver behavior at rural freeway work zone lane closure merge points, Center for Transportation Research and Education staff collected traffic data at merge areas using video image processing technology. The collection of data and the calculation of the capacity of lane closures are reported in a companion report, "Traffic Management Strategies for Merge Areas in Rural Interstate Work Zones". These data are used in the work reported in this document and are used to calibrate a microscopic simulation model of a typical, Iowa rural freeway lane closure. The model developed is a high fidelity computer simulation with an animation interface. It simulates traffic operations at a work zone lane closure. This model enables traffic engineers to visually demonstrate the forecasted delay that is likely to result when freeway reconstruction makes it necessary to close freeway lanes. Further, the model is also sensitive to variations in driver behavior and is used to test the impact of slow moving vehicles and other driver behaviors. This report consists of two parts. The first part describes the development of the work zone simulation model. The simulation analysis is calibrated and verified through data collected at a work zone in Interstate Highway 80 in Scott County, Iowa. The second part is a user's manual for the simulation model, which is provided to assist users with its set up and operation. No prior computer programming skills are required to use the simulation model.

Simulation of soybean growth and yield under northeastern Amazon climatic conditions

The objective of this work was to parameterize, calibrate, and validate a new version of the soybean growth and yield model developed by Sinclair, under natural field conditions in northeastern Amazon. The meteorological data and the values of soybean growth and leaf area were obtained from an agrometeorological experiment carried out in Paragominas, PA, Brazil, from 2006 to 2009. The climatic conditions during the experiment were very distinct, with a slight reduction in rainfall in 2007, due to the El Niño phenomenon. There was a reduction in the leaf area index (LAI) and in biomass production during this year, which was reproduced by the model. The simulation of the LAI had root mean square error (RMSE) of 0.55 to 0.82 m² m-2, from 2006 to 2009. The simulation of soybean yield for independent data showed a RMSE of 198 kg ha-1, i.e., an overestimation of 3%. The model was calibrated and validated for Amazonian climatic conditions, and can contribute positively to the improvement of the simulations of the impacts of land use change in the Amazon region. The modified version of the Sinclair model is able to adequately simulate leaf area formation, total biomass, and soybean yield, under northeastern Amazon climatic conditions.

Binding free energy differences in a TCR-peptide-MHC complex induced by a peptide mutation: a simulation analysis.

Recognition by the T-cell receptor (TCR) of immunogenic peptides presented by class I major histocompatibility complexes (MHCs) is the determining event in the specific cellular immune response against virus-infected cells or tumor cells. It is of great interest, therefore, to elucidate the molecular principles upon which the selectivity of a TCR is based. These principles can in turn be used to design therapeutic approaches, such as peptide-based immunotherapies of cancer. In this study, free energy simulation methods are used to analyze the binding free energy difference of a particular TCR (A6) for a wild-type peptide (Tax) and a mutant peptide (Tax P6A), both presented in HLA A2. The computed free energy difference is 2.9 kcal/mol, in good agreement with the experimental value. This makes possible the use of the simulation results for obtaining an understanding of the origin of the free energy difference which was not available from the experimental results. A free energy component analysis makes possible the decomposition of the free energy difference between the binding of the wild-type and mutant peptide into its components. Of particular interest is the fact that better solvation of the mutant peptide when bound to the MHC molecule is an important contribution to the greater affinity of the TCR for the latter. The results make possible identification of the residues of the TCR which are important for the selectivity. This provides an understanding of the molecular principles that govern the recognition. The possibility of using free energy simulations in designing peptide derivatives for cancer immunotherapy is briefly discussed.

Exercicis de física interactius

El present projecte pretén proposar una alternativa més per afrontar la física de 1r de Batxillerat. El resultat és una web amb una sèrie d'exercicis que mostren una solució implementada amb Box2D.

Effect of knotting on polymer shapes and their enveloping ellipsoids.

We simulate freely jointed chains to investigate how knotting affects the overall shapes of freely fluctuating circular polymeric chains. To characterize the shapes of knotted polygons, we construct enveloping ellipsoids that minimize volume while containing the entire polygon. The lengths of the three principal axes of the enveloping ellipsoids are used to define universal size and shape descriptors analogous to the squared radius of gyration and the inertial asphericity and prolateness. We observe that polymeric chains forming more complex knots are more spherical and also more prolate than chains forming less complex knots with the same number of edges. We compare the shape measures, determined by the enveloping ellipsoids, with those based on constructing inertial ellipsoids and explain the differences between these two measures of polymer shape.

Synchronization of symmetric chaotic systems

This paper contains a study of the synchronization by homogeneous nonlinear driving of systems that are symmetric in phase space. The main consequence of this symmetry is the ability of the response to synchronize in more than just one way to the driving systems. These different forms of synchronization are to be understood as generalized synchronization states in which the motions of drive and response are in complete correlation, but the phase space distance between them does not converge to zero. In this case the synchronization phenomenon becomes enriched because there is multistability. As a consequence, there appear multiple basins of attraction and special responses to external noise. It is shown, by means of a computer simulation of various nonlinear systems, that: (i) the decay to the generalized synchronization states is exponential, (ii) the basins of attraction are symmetric, usually complicated, frequently fractal, and robust under the changes in the parameters, and (iii) the effect of external noise is to weaken the synchronization, and in some cases to produce jumps between the various synchronization states available

Reaction-diffusion lattice gas: Theory and computer results

We report on the study of nonequilibrium ordering in the reaction-diffusion lattice gas. It is a kinetic model that relaxes towards steady states under the simultaneous competition of a thermally activated creation-annihilation $(reaction$) process at temperature T, and a diffusion process driven by a heat bath at temperature T?T. The phase diagram as one varies T and T, the system dimension d, the relative priori probabilities for the two processes, and their dynamical rates is investigated. We compare mean-field theory, new Monte Carlo data, and known exact results for some limiting cases. In particular, no evidence of Landau critical behavior is found numerically when d=2 for Metropolis rates but Onsager critical points and a variety of first-order phase transitions.

Chaotic systems with a null conditional Lyapunov exponent under nonlinear driving.

Control of a chaotic system by homogeneous nonlinear driving, when a conditional Lyapunov exponent is zero, may give rise to special and interesting synchronizationlike behaviors in which the response evolves in perfect correlation with the drive. Among them, there are the amplification of the drive attractor and the shift of it to a different region of phase space. In this paper, these synchronizationlike behaviors are discussed, and demonstrated by computer simulation of the Lorentz model [E. N. Lorenz, J. Atmos. Sci. 20 130 (1963)] and the double scroll [T. Matsumoto, L. O. Chua, and M. Komuro, IEEE Trans. CAS CAS-32, 798 (1985)].