Is simulation in health different?

It is often stated that health simulation is quite different and even that it is more difficult than in other sectors. But is simulation in health really different to simulation elsewhere? In this paper we explore this question through a survey of simulation modellers and academics. We elicit their opinions across a range of factors concerning the difficulties of health modelling against modelling in other domains. The analysis considers the responses of the whole group of respondents and the sub-group of respondents who have experience both in and outside of health modelling. The results show that overall, there is a perception that health modelling is different and that it is more difficult across a range of factors. The implications for simulation research and practice in health are discussed.     

Visual simulation in hospitals: A managerial or a political tool?

In hospitals, managerial change is often a matter of negotiation and discussion between medical, administrative and nursing disciplines. Any OR intervention should therefore: (a) be easily understandable by all concerned; (b) aid discussion of options. Visual interactive simulation meets these requirements. A complex of surgical services comprising several wards and operating theatres has been modelled, in such a way that movements of patients, variation in waiting lists, bed occupancy etc. can all be seen on a visual display screen. A simultaneous study of the managerial environment of the surgical unit has revealed the importance of internal politics, and the role which the simulation model may play in bids for resources. It is suggested that it is normal for OR projects to be used in this way. The implications for design of OR projects are discussed.     

Numerical simulation of blowup in nonlocal reaction–diffusion equations using a moving mesh method

In this paper we implement the moving mesh PDE method for simulating the blowup in reaction–diffusion equations with temporal and spacial nonlinear nonlocal terms. By a time-dependent transformation, the physical equation is written into a Lagrangian form with respect to the computational variables. The time-dependent transformation function satisfies a parabolic partial differential equation — usually called moving mesh PDE (MMPDE). The transformed physical equation and MMPDE are solved alternately by central finite difference method combined with a backward time-stepping scheme. The integration time steps are chosen to be adaptive to the blowup solution by employing a simple and efficient approach. The monitor function in MMPDEs plays a key role in the performance of the moving mesh PDE method. The dominance of equidistribution is utilized to select the monitor functions and a formal analysis is performed to check the principle. A variety of numerical examples show that the blowup profiles can be expressed correctly in the computational coordinates and the blowup rates are determined by the tests.     

Numerical simulation of metal removal in laser drilling using meshless local Petrov–Galerkin collocation method

A simplified 2D axisymmetric meshfree model of transient metal laser drilling is proposed for a continuous laser beam of Gaussian distribution. The penetration depth is predicted over the whole ablation time. The meshless local Petrov–Galerkin (MLPG) collocation method is used for discretizing the governing equation. Moving least square (MLS) and weighted least square (WLS) are used for approximating the local temperature field. The scheme is constructed in MATLAB, and the results are compared with previous numerical and experimental studies. The numerical results agree with the previous work, thus showing the models reliability in predicting the penetration depth for such a physically complex process.     

A Bernstein type theorem in ? × ? n

In this paper, as suitable application of the so-called Omori-Yau generalized maximum principle, we obtain a Bernstein type theorem concerning to complete hypersurfaces immersed with constant mean curvature in the product space ℝ × ℍ ⁿ . Furthermore, we treat the case that such hypersurfaces are vertical graphs.     

A Kuhnian Crisis in Management Science?

A survey of the Journal of the O.R. Society in 1978 shows that Ackoff's papers were part of a quite widespread and often pessimistic debate about the practical success of O.R. A similar survey for 1968 shows, on the other hand, a widespread mood of optimism. It is suggested that O.R. is now in a period of crisis analogous to that described by Kuhn in the Natural Sciences, when the dominant framework of assumptions appears to fail in relation to important problems. When such failures persist, alternative frameworks are proposed challenging the hitherto accepted view, and an increasingly wide-ranging debate develops. Many of the features of such debates, as outlined by Kuhn, seem to be present in the current controversy within O.R. More specifically, it seems possible in O.R. and related fields to identify three rival sets of proposals, which may be labelled official, reformist (e.g. Ackoffian) and revolutionary. However, the debate in O.R. differs from that in the Natural Sciences because it is not just about the best means of understanding the empirical world. It is also about the type of social world to be constructed through the framework of assumptions adopted. Our view is that in the current debate, proponents of the reformist stance will probably win. However, this may be very much an interim solution.     

An integrated fuzzy DEA–Fuzzy simulation approach for optimization of operator allocation with learning effects in multi products CMS

This paper presents an integrated fuzzy data envelopment analysis (FDEA) and fuzzy computer simulation approach for optimization of operator allocation in multi product cellular manufacturing systems (CMS) with learning effects. Operator allocation with learning effects is a challenging issue in flexible manufacturing systems in general and in CMS in particular. The main contribution of this work is taking into consideration various operators layouts and learning effects using fuzzy simulation and fuzzy DEA. FDEA is utilized to assess simulation alternatives in various levels of uncertainty. Previous studies consider only one type of product with crisp inputs, whereas this study considers multi-products and fuzzy set up times and processing times for CMS modeling. In addition, this study considers and integrates learning effects for optimum operators’ allocation. Moreover, more robust CMS assessment indicators are used in the proposed model. A case study illustrates the practicability, effectiveness and superiority of the proposed methodology.     

An epsilon-based measure of efficiency in DEA – A third pole of technical efficiency

In DEA, we have two measures of technical efficiency with different characteristics: radial and non-radial. In this paper we compile them into a composite model called “epsilon-based measure (EBM).” For this purpose we introduce two parameters which connect radial and non-radial models. These two parameters are obtained from the newly defined affinity index between inputs or outputs along with principal component analysis on the affinity matrix. Thus, EBM takes into account diversity of input/output data and their relative importance for measuring technical efficiency.     

A free lunch in chess and logic?

A café in Amsterdam. Claus and Connie are seated at the bar, finishing their drinks. They have been squabbling for much of the evening. Claus has taken a hard-boiled egg from a carousel and is spinning it distractedly on the counter. He places it in his coat pocket.     

A self-organized mesh generator using pattern formation in a reaction–diffusion system

A new type of mesh generator is developed by using a self-organized pattern in a reaction–diffusion system. The system is the Gray–Scott model, which creates a spot pattern in a specific parameter region. The spots correspond to nodes of a mesh. The mesh generator has several advantages: the algorithm is simple and processes to improve the mesh, such as smoothing, (locally) addition, and removal of nodes, are automatically performed by the system.     

Forecasting mortality in subpopulations using Lee–Carter type models: A comparison

The relative performance of multipopulation stochastic mortality models is investigated. When targeting mortality rates, we consider five extensions of the well known Lee–Carter single population extrapolative approach. As an alternative, we consider similar structures when mortality improvement rates are targeted. We use a dataset of deaths and exposures of Italian regions for the years 1974–2008 to conduct a comparison of the models, running a battery of tests to assess the relative goodness of fit and forecasting capability of different approaches. Results show that the preferable models are those striking a balance between complexity and flexibility.     

Effect of non‐normality on the power in analysis of variance: A simulation study

The use of simulation methods for calculating the power values in the case of non‐normal errors is discussed. One and two‐way layouts are considered for the fixed effect model. The Erlangian and contaminated normal distribution are taken as examples of a non‐normal error distribution. The results obtained by these methods are given in tables 1 and 2 which indicate that for inference concerning means the power calculated under normal theory is only slightly affected by the non‐normality of the errors.     

Chapter 12 New uses of DEA and statistical regressions for efficiency evaluation and estimation — with an illustrative application to public secondary schools in Texas

This paper examines new combinations of Data Envelopment Analysis (DEA) and statistical approaches that can be used to evaluate efficiency within a multiple-input multiple-output framework. Using data on five outputs and eight inputs for 638 public secondary schools in Texas, unsatisfactory results are obtained initially from both Ordinary Least Squares (OLS) and Stochastic Frontier (SF) regressions run separately using one output variable at-a-time. Canonical correlation analysis is then used to aggregate the multiple outputs into a single aggregate output, after which separate regressions are estimated for the subsets of schools identified as efficient and inefficient by DEA. Satisfactory results are finally obtained by a joint use of DEA and statistical regressions in the following manner. DEA is first used to identify the subset of DEA-efficient schools. The entire collection of schools is then comprehended in a single regression with dummy variables used to distinguish between DEA-efficient and DEA-inefficient schools. The input coefficients are positive for the efficient schools and negative and statistically significant for the inefficient schools. These results are consistent with what might be expected from economic theory and are informative for educational policy uses. They also extend the treatments of production functions usually found in the econometrics literature to obtain one regression relation that can be used to evaluate both efficient and inefficient behavior.     

How to generate regularly behaved production data? A Monte Carlo experimentation on DEA scale efficiency measurement

Monte Carlo experimentation is a well-known approach used to test the performance of alternative methodologies under different hypotheses. In the frontier analysis framework, whatever the parametric or non-parametric methods tested, experiments to date have been developed assuming single output multi-input production functions. The data generated have mostly assumed a Cobb–Douglas technology. Among other drawbacks, this simple framework does not allow the evaluation of DEA performance on scale efficiency measurement. The aim of this paper is twofold. On the one hand, we show how reliable two-output two-input production data can be generated using a parametric output distance function approach. A variable returns to scale translog technology satisfying regularity conditions is used for this purpose. On the other hand, we evaluate the accuracy of DEA technical and scale efficiency measurement when sample size and output ratios vary. Our Monte Carlo experiment shows that the correlation between true and estimated scale efficiency is dramatically low when DEA analysis is performed with small samples and wide output ratio variations.     

A bending–stretching model in adhesive contact for elastic rods obtained by using asymptotic methods

This paper is devoted to the derivation and mathematical justification of models for the bending–stretching of an elastic rod in adhesive contact with a deformable foundation. The process is assumed to be quasistatic, and therefore the effects of inertia are neglected. Contact is modeled with normal compliance and the adhesion is modeled by introducing a surface internal variable, the bonding function, the evolution of which is described by an ordinary differential equation. To derive the models we consider the three-dimensional contact problem of an elastic body in adhesive contact with a foundation, introduce a change of variable together with the scaling of the unknowns and parameters of the problem, and we obtain a limit model under the assumption of suitable asymptotic expansions for the scaled unknowns. After that, we obtain error estimates and convergence results which legitimate the limit model. Finally we show that our limit model contains as particular cases models previously considered by other authors. To our knowledge it is for the first time that a rigorous justification and a generalization of those models is provided.     

An improvement on the Tracy and Chen model ‘A generalized model for weight restrictions in DEA’

Recently Tracy and Chen presented a parametric DEA model (PDEA) to assess relative efficiency in the presence of a generalized form of linear weight restrictions. This paper proposes a modification to the PDEA model that avoids the need to resort to searching algorithms to estimate efficiency, and assures that the correct efficiency scores are obtained in a single stage using mathematical programming solvers. The results of this model and the results of Tracy and Chen's PDEA model are compared using the examples reported in their paper. The results confirm the superiority of the model proposed in this paper.     

Can R&D expenditure avoid corporate bankruptcy? Comparison between Japanese machinery and electric equipment industries using DEA–discriminant analysis

This study compares data envelopment analysis–discriminant analysis (DEA–DA) with Altman’s financial ratio analysis to identify the position of DEA–DA in financial performance analysis. Then, this study applies DEA–DA to examine whether Research and Development (R&D) expenditure influences the financial performance of Japanese machinery industry and electric equipment industry. The investigation of DEA–DA identifies that the R&D expenditure makes a positive impact on the financial performance of Japanese machinery industry, but it yields a negative impact on Japanese electric equipment industry. The result implies that the influence of R&D expenditure on financial performance (including the avoidance of bankruptcy) depends upon the type of a manufacturing industry. A rationale regarding why such a discrepancy has occurred between the two Japanese manufacturing industries is because the life cycle of electric equipments is shorter than that of the machinery products. Furthermore, the electric equipment industry faces more fierce competition than the machinery industry. This study suggests that the Japanese electric equipment industry needs R&D expenditure for competition in its global market. However, it is a high risk and high return investment. In contrast, the Japanese machinery is a technologically mature industry where the R&D expenditure influences positively its financial performance. In this sense, the R&D expenditure is a low risk and necessary investment.     

Natural selection: A concept in need of some evolution?

In some respects natural selection is a quite simple theory, arrived at through the logical integration of three propositions (the presence of variation within natural populations, an absolutely limited resources base, and procreation capacities exceeding mere replacement numbers) whose individual truths can hardly be denied. Its relation to the larger subject of evolution, however, remains problematic. It is suggested here thata scaling‐down of the meaning of natural selection to “the elimination of the unfit,” as originally intended by Alfred Russel Wallace (1823–1913), might ultimately prove a more effective means of relating it to larger‐scale, longer‐term, evolutionary processes. © 2011 Wiley Periodicals, Inc. Complexity, 2011