A group based solution strategy for multi-physics simulations in parallel

Multi-physics simulation often requires the solution of a suite of interacting physical phenomena, the nature of which may vary both spatially and in time. For example, in a casting simulation there is thermo-mechanical behaviour in the structural mould, whilst in the cast, as the metal cools and solidifies, the buoyancy induced flow ceases and stresses begin to develop. When using a single code to simulate such problems it is conventional to solve each ‘physics’ component over the whole single mesh, using definitions of material properties or source terms to ensure that a solved variable remains zero in the region in which the associated physical phenomenon is not active. Although this method is secure, in that it enables any and all the ‘active’ physics to be captured across the whole domain, it is computationally inefficient in both scalar and parallel. An alternative, known as the ‘group’ solver approach, involves more formal domain decomposition whereby specific combinations of physics are solved for on prescribed sub-domains. The ‘group’ solution method has been implemented in a three-dimensional finite volume, unstructured mesh multi-physics code, which is parallelised, employing a multi-phase mesh partitioning capability which attempts to optimise the load balance across the target parallel HPC system. The potential benefits of the ‘group’ solution strategy are evaluated on a class of multi-physics problems involving thermo-fluid–structural interaction on both a single and multi-processor systems. In summary, the ‘group’ solver is a third faster on a single processor than the single domain strategy and preserves its scalability on a parallel cluster system.     

Selecting predictors for traffic control by methods of the mathematical theory of democracy

The mathematical theory of democracy operates on the indices of popularity and universality which are used to find socially optimal representatives and representative bodies. Regarded mathematically, neither the ‘society’, nor its ‘representatives’ are necessarily human, so that some objects can represent the behavior of other objects. This idea is applied to selecting predictors of traffic jams which occur the City Ring of Hagen, Germany; the traffic situations at street intersections all over the town are regarded as representatives of future traffic situations at the Ring intersections. As a result, a reliable prediction can be attained by already five surveillance cameras installed at appropriate locations. The selection of such locations and processing the data captured by the cameras constitute the subjects of this paper.     

SSM and technology management: Developing multimethodology through practice

Growing competition and economic recession is driving the need for more rapid redesign of operations enabled by innovative technologies. The acquisition, development and implementation of systems to manage customer complaints and control the quality assurance process is a critical area for engineering and manufacturing companies. Multimethodologies, and especially those that can bridge ‘soft’ and ‘hard’ OR practices, have been seen as a possible means to facilitate rapid problem structuring, the analysis of alternative process design and then the specification through to implementation of systems solutions. Despite the many ‘hard’ and ‘soft’ OR problem structuring and management methods available, there are relatively few detailed empirical research studies of how they can be combined and conducted in practice. This study examines how a multimethodology was developed, and used successfully, in an engineering company to address customer complaints/concerns, both strategically and operationally. The action research study examined and utilised emerging ‘soft’ OR theory to iteratively develop a new framework that encompasses problem structuring through to technology selection and adoption. This was based on combining Soft Systems Methodology (SSM) for problem exploration and structuring, learning theories and methods for problem diagnosis, and technology management for selecting between alternatives and implementing the solution. The results show that, through the use of action research and the development of a contextualised multimethodology, stakeholders within organisations can participate in the design of new systems and more rapidly adopt technology to address the operational problems of customer complaints in more systemic, innovative and informed ways.     

A closer look at the economic-environmental disparities for regional development in China

Although China has harvested the fruits of its rapid economic growth over a period of several decades, it has encountered serious environmental problems, an important one being air pollution in the form of soot, dust, and sulfur dioxide. In considering the concept of ‘green-GDP’, this paper analyzes China’s regional development by examining its economic performance while taking into account various environmental factors. In addition to computing technical efficiency for 31 regions in China, a cross-efficiency measure is applied to differentiate the genuine DMUs. ‘Overall’ efficient regions and ‘false positive’ ones are recognized by a false positive index (FPI). It is found that the coastal regions perform on average better than the inland regions both economically and environmentally. For inefficient regions, the benchmark should be those regions with high cross-efficiency mean scores (e.g., Guangdong) rather than those with high self-appraisal scores (e.g., Shanghai). A cross-tabulation illustrating the difference between GDP-oriented performance and Pollution-oriented performance shows that the coastal regions make up the dominant proportion in terms of the benchmarks for economic-environmental optimization.     

A binary particle swarm optimization algorithm inspired by multi-level organizational learning behavior

Recently, nature-inspired algorithms have increasingly attracted the attention of researchers. Due to the fact that in BPSO the position vectors consisting of ‘0’ and ‘1’ can be seen as a decision behavior (support or oppose), in this paper, we propose a BPSO with hierarchical structure (BPSO_HS for short), on the basis of multi-level organizational learning behavior. At each iteration of BPSO_HS, particles are divided into two classes, named ‘leaders’ and ‘followers’, and different evolutionary strategies are used in each class. In addition, the mutation strategy is adopted to overcome the premature convergence and slow convergent speed during the later stages of optimization. The algorithm was tested on two discrete optimization problems (Traveling Salesman and Bin Packing) as well as seven real-parameter functions. The experimental results showed that the performance of BPSO_HS was significantly better than several existing algorithms.     

On Klein’s icosahedral solution of the quintic

We present an exposition of the icosahedral solution of the quintic equation first described in Klein’s classic work ‘Lectures on the icosahedron and the solution of equations of the fifth degree’. Although we are heavily influenced by Klein we follow a slightly different approach which enables us to arrive at the solution more directly.     

A hybrid placement strategy for the three-dimensional strip packing problem

This paper presents a hybrid placement strategy for the three-dimensional strip packing problem which involves packing a set of cuboids (‘boxes’) into a three-dimensional bin (parallelepiped) of fixed width and height but unconstrained length (the ‘container’). The goal is to pack all of the boxes into the container, minimising its resulting length. This problem has potential industry application in stock cutting (wood, polystyrene, etc. – minimising wastage) and also cargo loading, as well as other applications in areas such as multi-dimensional resource scheduling. In addition to the proposed strategy a number of test results on available literature benchmark problems are presented and analysed. The results of empirical testing of the algorithm show that it out-performs other methods from the literature, consistently in terms of speed and solution quality-producing 28 best known results from 35 test cases.     

An integrated performance evaluation of financial holding companies in Taiwan

There has been a worldwide trend for financial institutions to become larger in scale and more diversified in scope, with Taiwan being no exception. Fourteen financial holding companies (FHCs) have each begun to function as a management umbrella in Taiwan by investing in different types of financial services such as banking, insurance, and securities. This paper focuses on this local financing issue from an integrated methodological perspective by model innovations proposed in several earlier studies. For example, the efficiency of profitability and marketability are combined to evaluate the FHCs’ performance. To conduct a valid and reliable evaluation process while applying the FHC’s case in Taiwan, we integrate the slacks-based measure (SBM) and slacks-based measure of super efficiency (super-SBM) models in order to directly handle the slacks and identify the best performers. A new scheme that deals with the negative output data in the SBM/super-SBM is also introduced. Inter-temporal efficiency change, which is decomposed into ‘catch-up’ and ‘frontier-shift’ effects, is analyzed by means of the SBM-based Malmquist index. A decision-making matrix is also presented to help the FHCs’ managerial authorities position themselves in the industry. The above techniques show with a high degree of consistency that large-sized FHCs perform better than small-sized ones.     

Observations on the tanh-coth expansion method for finding solutions to nonlinear evolution equations

The ‘tanh-coth expansion method’ for finding solitary travelling-wave solutions to nonlinear evolution equations has been used extensively in the literature. It is a natural extension to the basic tanh-function expansion method which was developed in the 1990s. It usually delivers three types of solution, namely a tanh-function expansion, a coth-function expansion, and a tanh-coth expansion. It is known that, for every tanh-function expansion solution, there is a corresponding coth-function expansion solution. It is shown that there is a tanh-coth expansion solution that is merely a disguised version of the coth solution. In many papers, such tanh-coth solutions are erroneously claimed to be ‘new’. However, other tanh-coth solutions may be delivered that are genuinely new in the sense that they would not be delivered via the basic tanh-function method. Similar remarks apply to tan, cot and tan-cot expansion solutions.     

Ordering policy and coordination of a supply chain with two-period demand uncertainty

We develop a two-period game model of a one-manufacturer and one-retailer supply chain to investigate the optimal decisions of the players, where stock-out and holding costs are incorporated into the model. The demand at each period is stochastic and price sharply drops in mid-life. We assume the retailer has a single order opportunity, and decides how much inventory to keep in the middle of selling season. We show that both the price-protection mid-life and end-of-life returns (PME) scheme and the only mid-life and end-of-life returns (ME) scheme may achieve channel coordination and access a ‘win-win’ situation under some conditions. The larger the lowest expected profit of the retailer, the lower the possibility of ‘win-win’ situation will be. Combined with the analysis of feasible regions for coordination policies, we find that PME scheme is not always better than ME scheme from the perspective of implementable mechanism. Finally, we find that adopting the dispose-down-to (DDT) policy can bring a larger improvement of the expected channel profit in the centralized setting, and it is interesting that by using DDT policy, double marginalization occurs only at Period 1, and however, does not plague the retailer in Period 2.     

A splitting technique of higher order for the Navier–Stokes equations

This article presents a splitting technique for solving the time dependent incompressible Navier–Stokes equations. Using nested finite element spaces which can be interpreted as a postprocessing step the splitting method is of more than second order accuracy in time. The integration of adaptive methods in space and time in the splitting are discussed. In this algorithm, a gradient recovery technique is used to compute boundary conditions for the pressure and to achieve a higher convergence order for the gradient at different points of the algorithm. Results on the ‘Flow around a cylinder’s- and the ‘Driven Cavity’s-problem are presented.     

Auditors’ evidence evaluation and aggregation using beliefs and probabilities

This paper examines possible differences in auditors’ performance when they make belief-based versus probability-based risk assessments by focusing on two phases of the financial statement audit process: the assessment of two attributes of audit evidence (‘strength’ and ‘direction’) and the aggregation of evidence. Based on an experiment in which 48 experienced auditors participated, three important findings were observed. First, there was no significant difference in the mean assessment of strength of evidence measured using the likelihood ratio. However, the difference in the assessed direction of evidence, that is whether the evidence is interpreted as being confirming or disconfirming, is significant for one of the cases examined. This result shows that auditors making belief-based assessments are able to assess the direction of the evidence more accurately than auditors making probability-based assessments. Third, the auditors’ aggregation of evidence was not in accordance with ‘AND’ logic for either auditors making belief-based or probability-based assessments. These empirical results raise issues which need to be addressed in practice and in future research.     

Interpolation in Bernstein and Paley-Wiener spaces

We consider interpolation of discrete functions by continuous ones with restriction on the size of spectra. We discuss a sharp contrast between the cases of compact and unbounded spectra. In particular we construct ‘universal’ spectra of small measure which deliver positive solution of the interpolation problem in Bernstein spaces for every discrete sequence of knots.     

Basic randomness of nature and ether-drift experiments

We re-consider the idea that quantum fluctuations might reflect the existence of an ‘objective randomness’, i.e. a basic property of the vacuum state which is independent of any experimental accuracy of the observations or limited knowledge of initial conditions. Besides being responsible for the observed quantum behavior, this might introduce a weak, residual form of ‘noise’ which is intrinsic to natural phenomena and could be important for the emergence of complexity at higher physical levels. By adopting Stochastic Electro Dynamics as a heuristic model, we are driven to a picture of the vacuum as a form of highly turbulent ether, which is deep-rooted into the basic foundational aspects of both quantum physics and relativity, and to search for experimental tests of this scenario. An analysis of the most precise ether-drift experiments, operating both at room temperature and in the cryogenic regime, shows that, at present, there is some ambiguity in the interpretation of the data. In fact the average amplitude of the signal has precisely the magnitude expected, in a ‘Lorentzian’ form of relativity, from an underlying stochastic ether and, as such, might not be a spurious instrumental effect. This puzzle, however, should be solved in a next future with the use of new cryogenically cooled optical resonators whose stability should improve by about two orders of magnitude. In these new experimental conditions, the persistence of the present amplitude would represent a clean evidence for the type of random vacuum we are envisaging.     

A two-echelon base-stock inventory model with Poisson demand and the sequential processing of orders at the upper echelon

We consider a two-echelon inventory system with a number of non-identical, independent ‘retailers’ at the lower echelon and a single ‘supplier’ at the upper echelon. Each retailer experiences Poisson demand and operates a base stock policy with backorders. The supplier manufactures to order and holds no stock. Orders are produced, in first-come first-served sequence, with a fixed production time. The supplier therefore functions as an M/D/1 queue. We are interested in the performance characteristics (average inventory, average backorder level) at each retailer. By finding the distribution of order lead time and hence the distribution of demand during order lead time, we find the steady state inventory and backorder levels based on the assumption that order lead times are independent of demand during order lead time at a retailer. We also propose two alternative approximation procedures based on assumed forms for the order lead time distribution. Finally we provide a derivation of the steady state inventory and backorder levels which will be exact as long as there is no transportation time on orders between the supplier and retailers. A numerical comparison is made between the exact and approximate measures. We conclude by recommending an approach which is intuitive and computationally straightforward.     

Diagnostic assessment of children’s proportional reasoning

A proportional reasoning item bank was created from the relevant literature and tested in various forms. Rasch analyses of 303 pupils’ test results were used to calibrate the bank, and data from 84 pupils’ interviews was used to confirm our diagnostic interpretations. A number of sub-tests were scaled, including parallel ‘without models’ and ‘with models’ forms. We provide details of the 13-item ‘without models’ test which was formed from the ‘richest’ diagnostic items and verified on a further test sample (N=212, ages 10-13). Two scales were constructed for this test, one that measures children’s ‘ratio attainment’ and one that measures their ‘tendency for additive strategy.’ Other significant errors — ‘incorrect build-up,’ ‘magical doubling/halving,’ ‘constant sum’ and ‘incomplete reasoning’ — were identified. Finally, an empirical hierarchy of pupils’ attainment of proportional reasoning was formed, incorporating the significant errors and the additive scale.     

An iterated Radau method for time-dependent PDEs

This paper is concerned with the time integration of semi-discretized, multi-dimensional PDEs of advection-diffusion-reaction type. To cope with the stiffness of these ODEs, an implicit method has been selected, viz., the two-stage, third-order Radau IIA method. The main topic of this paper is the efficient solution of the resulting implicit relations. First, a modified Newton process has been transformed into an iteration process in which the 2 stages are decoupled and, moreover, can exploit the same LU-factorization of the iteration matrix. Next, we apply a so-called Approximate Matrix Factorization (AMF) technique to solve the linear systems in each Newton iteration. This AMF approach is very efficient since it reduces the ‘multi-dimensional’ system to a series of ‘one-dimensional’ systems. The total amount of linear algebra work involved is reduced enormously by this approach. The idea of applying AMF to two-dimensional problems is quite old and goes back to Peaceman and Rachford in the early fifties. The situation in three space dimensions is less favourable and will be analyzed here in more detail, both theoretically and experimentally. Furthermore, we analyze a variant in which the AMF-technique has been used to really solve (‘until convergence’) the underlying Radau IIA method so that we can rely on its excellent stability and accuracy characteristics. Finally, the method has been tested on several examples. Also, a comparison has been made with the existing codes VODPK and IMEXRKC, and the efficiency (CPU time versus accuracy) is shown to be at least competitive with the efficiency of these solvers.     

A meshless based numerical technique for traveling solitary wave solution of Boussinesq equation

In this paper, we employ the boundary-only meshfree method to find out numerical solution of the classical Boussinesq equation in one dimension. The proposed method in the current paper is a combination of boundary knot method and meshless analog equation method. The boundary knot technique is an integration free, boundary-only, meshless method which is used to avoid the known disadvantages of the method of fundamental solution. Also, we use the meshless analog equation method to replace the nonlinear governing equation with an equivalent nonhomogeneous linear equation. A predictor-corrector scheme is proposed to solve the resulted differential equation of the collocation. The numerical results and conclusions are obtained for both the ‘good’ and the ‘bad’ Boussinesq equations.     

Predicting DAX trends from Dow Jones data by methods of the mathematical theory of democracy

The mathematical theory of democracy operates on the indices of popularity and universality which are used to find socially optimal representatives and representative bodies. Regarded mathematically, neither the ‘society’, nor its ‘representatives’ are necessarily human, so that some objects can represent the behavior of other objects. This idea is applied to predicting the DAX-trends (German stock index) from the actual Dow-Jones data; the current fluctuations of stock prices in New York are regarded as representative indicators of future stock price fluctuations in Frankfurt. In particular, it is found that American Express anticipates on the average the price ±fluctuations of 2/3 of the DAX stocks. The statistical significance of the null hypothesis that such a bias from the uncertainty 50% can occur by chance is only 3.5%.     

Norm statistics and the complexity of clustering problems

In this paper we introduce a new class of clustering problems. These are similar to certain classical problems but involve a novel combination of ?_p-statistics and ?_q norms. We discuss a real world application in which the case p=2 and q=1 arises in a natural way. We show that, even for one dimension, such problems are NP-hard, which is surprising because the same 1-dimensional problems for the ‘pure’ ?₂-statistic and ?₂ norm are known to satisfy a ‘string property’ and can be solved in polynomial time. We generalize the string property for the case p=q. The string property need not hold when q≤p−1 and we show that instances may be constructed, for which the best solution satisfying the string property does arbitrarily poorly. We state some open problems and conjectures.