The design and analysis of a generalized RESTART/DPR algorithm for rare event simulation

We consider a general class of branching methods with killing for the estimation of rare events. The class includes a number of existing schemes, including RESTART and DPR (Direct Probability Redistribution). A method for the design and analysis is developed when the quantity of interest can be embedded in a sequence whose limit is determined by a large deviation principle. A notion of subsolution for the related calculus of variations problem is introduced, and two main results are proved. One is that the number of particles and the total work scales subexponentially in the large deviation parameter when the branching process is constructed according to a subsolution. The second is that the asymptotic performance of the schemes as measured by the variance of the estimate can be characterized in terms of the subsolution. Some examples are given to demonstrate the performance of the method.     

On the use of reduced-order models and simulation data in control-system design

This note extends some results on robust control and approximation,to provide a systematic framework for the use of reduced-ordermodels of single-input single-output systems in control systemsdesign where data from a finite number of simulations of theoriginal open-loop system can be used to assess the stabilityand performance of the implemented closed-loop scheme and substantiallyreduce conservatism during the design stage without the needfor a full closed-loop plant simulation.     

The use of the simplex method in the design of parachute systems with use of a prototype

We develop a formal mathematical apparatus that makes it possible using the simplex method (linear programming) to carry out the design of parachute systems with use of a prototype, the experimental development of parachute systems using a computer, the analysis of a technical problem, and the identification of mathematical models of an automated parachute design system.Translated fromDinamicheskie Sistemy, No. 6, 1987, pp. 46–49.     

Development of a fuzzy-expert system for incident detection and classification

This research presents the exploratory results of using fuzzy-expert systems for incident detection and classification. The proposed system functions to detect not only the occurrence of incidents, but also their located lanes, and the resulting type of severity. With such information, the traffic control center can better advise drivers to take necessary lane changes and take timely actions for minimizing the incident impacts on traffic conditions. Although the current research remains exploratory in nature, as both the fuzzy membership functions and key parameters were determined empirically rather than fine-tuned with a neural network or genetic algorithm, the preliminary results have confirmed the promising properties of the proposed system.     

Modeling of loss aversion in solving fuzzy road transport traveling salesman problem using eugenic bacterial memetic algorithm

The aim of the traveling salesman problem (TSP) is to find the cheapest way of visiting all elements in a given set of cities and returning to the starting point. In solutions presented in the literature costs of travel between nodes (cities) are based on Euclidean distances, the problem is symmetric and the costs are constant and crisp values. Practical application in road transportation and supply chains are often fuzzy. The risk attitude depends on the features of the given operation. The model presented in this paper handles the fuzzy, time dependent nature of the TSP and also gives solution for the asymmetric loss aversion by embedding the risk attitude into the fitness function of the bacterial memetic algorithm. Computational results are presented as well.     

The use of simulation in validating a multiobjective EMS location model

A location model is proposed for emergency medical service systems to solve the multiobjective location problem of minimizing mean response time and balancing facility workload. Location solutions generated from the model are tested with simulation and are shown to be quite realistic with regard to mean response time prediction and facility allocation. This efficiency is determined to be directly attributable to workload constraints.     

The use of search experimentation in discrete-event simulation practice

The practice of DES experimentation has not been rigorously assessed in over a decade. Past studies of DES practice report little transfer of experimentation theory into real-world application. We conducted an international survey of over 300 modellers to investigate the extent to which simulation optimisation, meta-modelling and design of experiments are used in practice. Over the last decade there has been substantial growth in the use of optimisation and to a lesser extent design of experiments to tackle practical problems. However, users rarely make use of optimisers bundled with commercial software, opting instead for custom or third-party solutions. Outside of academia, the use of methods is hampered by a lack of application knowledge and a persisting view that such techniques are not necessary. It is clear that academics must not become complacent regarding the dissemination of theory into common practice and continue to reach out to industry users.     

Two-dimensional time-dependent simulation of contaminant transport from a landfill

A numerical model to simulate solute transport in flowing groundwater is developed using finite-difference solutions to the groundwater flow equation and the solute transport equation.The use of the model is illustrated by its application to a problem of groundwater contamination in a waste-disposal area in Miami, Florida. The model integrates the effects of several factors that controlled changes in iron concentrations, and successfully reproduced the record of contamination observed during a one-year period.The model was found to be insensitive to chemical parameters, but sensitive to an aquifer dispersion coefficient and the groundwater flow velocity. This implies that there can be sites where the chemical attenuation can be approximated without a significant impact on results.     

The design of an efficient load balancing algorithm employing block design

In order to maintain load balancing in a distributed system, we should obtain workload information from all the nodes on network. This processing requiresO(v ²) communication overhead, wherev is the number of nodes. In this paper, we present a new synchronous dynamic distributed load balancing algorithm on a (v, k+1, 1)-configured network applying a symmetric balanced incomplete block design, wherev=k ²+k+1. Our algorithm needs only $O(v\sqrt v )$ communication overhead and each node receives workload information from all the nodes without redundancy. Therefore, load balancing is maintained since every link has the same amount of traffic for transferring workload information.     

The use of QP-free algorithm in the limit analysis of slope stability

In many mountainous areas, landslides and slope instabilities frequently occur after heavy rainfall and earthquake, and result in enormous casualties and huge economic losses. In order to mitigate the landslides hazard efficiently, a method is required for a better understanding of stability analysis. Fortunately, upper bound theorem of limit analysis provides a practical and effective upper bound approach to evaluate the stability of slopes. And in this approach, the search for the minimum factor of safety can be formulated as a nonlinear constrained optimization. In general, the SQP-type algorithms are used to solve this optimization problem. However, it is quite time consuming and difficult to search the optimum from an arbitrary starting point based on the SQP-type algorithms. Fortunately, a QP-free algorithm based on penalty function and active-set strategy can be globally convergent toward the KKT points with arbitrary starting point, and the rate of convergence is local superlinear or even quadratic. Two classical problems of slope stability are solved by this QP-free algorithm. The results show that the QP-free algorithm would be the better choice than SQP-type algorithms for solving the nonlinear constrained optimization problem which is derived from the upper bound limit analysis of slope stability.     

Disruption management in vehicle routing and scheduling for road freight transport: a review

Disruption management is an approach to the rescheduling of operations following an unanticipated event occurring that has been applied in a wide range of applications, including airline scheduling and project management. This review focusses on the use of disruption management in vehicle routing and scheduling applied to road freight distribution. The paper discusses the key features of disruption management and examines the relevant objectives and types of disruption that may occur in this context. Different formulations and solution methods are described. A set of relevant papers are summarised and classified according to the type of disruption addressed, the relevant objectives and the solution approach.     

A study of a numerical algorithm for a nonlinear transport model

For a nonlinear transport model, we propose a simple and economical two-step algorithm that decreases the dimension of the system of nonlinear equations, as compared with implicit difference schemes. We prove theorems on necessary conditions for stability with respect to the initial data for the nonlinear problem and theorems on sufficient conditions for stability in the case of the linearized model. We also obtain theorems on approximation of the integral conservation law on a grid. The necessary condition obtained is a condition on the coefficients of the differential equation (which singles out an admissible class of equations) but not a condition on the ratio of the grid steps. Bibliography: 3 titles. Translated fromObchyslyuval'na ta Prykladna Matematyka, No. 81, 1997, pp. 25–32.     

Clique detection in directed graphs: a new algorithm

A new algorithm for clique-detection in a graph is introduced. The method rests on the so-called “decomposition of a graph into a chain of subgraphs” and on the corresponding so-called “quasi-blockdiagonalisation” of the adjacency matrix. A FORTRAN IV computer-program is presented.     

The use of order statistic numerical simulation algorithms

A modification of the standard algorithm for the simulation of order statistics for a uniform distribution is proposed that uses confidence intervals. It is found that one of the applications of the algorithms for the simulation of order statistics (namely, simulation of the beta distribution with integer parameters) gives more efficient methods for the simulation of order statistics than the algorithm based on confidence intervals. It is shown that the resulting algorithm can be used for the efficient simulation of random variables with polynomial density and of beta distributed random variables with large noninteger parameters.     

Modelling and simulation of heat exchange and transport in a geothermal plant

The production of energy by use of the high temperature in the earth's mantle has played an increasingly important role in recent years. However, large uncertainties concerning the conditions in the subsurface make it difficult to use power plants efficiently. An appropriate modelling and simulation of the heat exchange and transport provides a promising tool for further investigations of the process and optimisation of the productivity. Starting from the isothermal state at high temperatures, a cold fluid is injected through a borehole into a porous rock by applying a pressure difference between at least two wells. Passing the fractured rock, the water is heated at the crack interfaces. In addition to the convection of the temperature due to the water flow, the conduction of heat in the rock and the water has to be considered. The modelling approach of this coupled process is based on the Theory of Porous Media (TPM). Both, the rock and the water, are assumed to be materially incompressible and the thermal expansion is solely considered for the fluid, since the expansion of the rock is negligible for the occurring temperature differences. Furthermore, it is assumed that the subsurface is saturated with water. To solve the generated initial-boundary-value problem, the governing primary variables of the coupled model are spatially approximated by mixed finite elements and the time discretisation is carried out by an implicit Euler time-integration scheme. Since in the considered problem the convective transport is dominant, a streamline upwinding scheme is used for the numerical stabilisation to obtain non-oscillatory solutions. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Use of artificial neural network simulation metamodelling to assess groundwater contamination in a road project

The estimation of the extent of a polluted zone after an accidental spill occurred in road transport is essential to assess the risk of water resources contamination and to design remediation plans. This paper presents a metamodel based on artificial neural networks (ANN) for estimating the depth of the contaminated zone and the volume of pollutant infiltration in the soil in a two-layer soil (a silty cover layer protecting a chalky aquifer) after a pollutant discharge at the soil surface. The ANN database is generated using USEPA NAPL-Simulator. For each case the extent of contamination is computed as a function of cover layer permeability and thickness, water table depth and soil surface–pollutant contact time. Different feedforward artificial neural networks with error backpropagation (BPNN) are trained and tested using subsets of the database, and validated on yet another subset. Their performance is compared with a metamodelling method using multilinear regression approximation. The proposed ANN metamodel is used to assess the risk for a DNAPL pollution to reach the groundwater resource underneath the road axis of a highway project in the north of France.     

Numerical simulation of the turbulent boundary layer equations via a Runge-Kutta algorithm

This paper addresses a hybrid computational procedure for the step-by-step calculation of momentum transfer in turbulent boundary layer flows along flat plates. The proposed procedure relies on a modified method of lines wherein transversal discretizations are carried out by a “control volume” being infinitesimal in the streamwise direction and finite in the transversal direction of the fluid flow. Using mixing length theory and coarse intervals in the transversal direction, the resulting system of ordinary differential equations of first order may be readily integrated on a personal computer utilizing a fourth-order Runge-Kutta algorithm. In general, a maximum number of sixteen lines is necessary at the trailing edge of the flat plate for a typical calculation. As a consequence, computing time and storage for each run were very small when compared to other finite-difference methods. Furthermore, to validate the hybrid procedure involving the method of lines and control volumes (MOLCV), comparisons with experimental data have been done in terms of both velocity distributions and local skin friction coefficients. For all cases tested, the proposed methodology predicts the growth of the boundary layer of gases correctly.