Designing Effective Simulation-based Decision Support Systems: An Empirical Assessment of Three Types of Decision Support Systems

This paper addresses the design of effective simulation-based decision support systems (DSS). An experiment was conducted using three different DSS tools developed around three types of simulation model—traditional, conventional visual interactive simulation (VIS), and ‘paired-systems’ VIS. Subjects were asked to perform a decision making task and their performance was evaluated. Subjects who used the DSS based on a ‘paired systems’ VIS model were found to be both the most effective and the most efficient at the problem-solving task. Subjects provided with the DSS based upon a conventional VIS model were found to be more effective at the task than the group provided with the traditional simulation-based DSS.     

Knowledge-based improvement: simulation and artificial intelligence for identifying and improving human decision-making in an operations system

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as ‘knowledge-based improvement’ (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.     

Modelling,simulation, animation,and real-time control (MoSART) for a class of electromechanical systems: a system-theoretic approach

This paper describes an interactive modelling, simulation, animation, and real-time control (MoSART) environment for a class of ‘cart-pendulum’ electromechanical systems that may be used to enhance learning within differential equations and linear algebra classes. The environment is useful for conveying fundamental mathematical/systems concepts through computer-aided analysis, design, graphical visualization, and 3D animation. Referred to as Cart-Pendulum Control3D-Lab1Control3D-Lab-short for control 3D animation laboratory. The author to whom correspondence should be addressed., the environment is based on Microsoft Windows/Visual C++/Direct-3D and MATLAB/Simulink2MATLAB and Simulant are trademarks of The Masterworks, Inc.. Pull-down menus provide access to systems/models/control laws, exogenous signals, parameters, animation models and visual indicators, a suite of (easy-to-modify) Simulant diagrams containing models and control laws, MATLAB m-files for detailed analysis and design, and detailed documentation for each of the above. Three blocks enable animation, joystick inputs, and real-time animation within Simulant. Examples are presented to illustrate the utility of the environment as a valuable tool for analysing/visualizing the above class of electromechanical systems and for enhancing mathematics instruction.     

Digital maps,matrices and computer algebra

The way in which computer algebra systems, such as Maple®, have made the study of complex problems accessible to undergraduate mathematicians with modest computational skills is illustrated by some large matrix calculations, which arise from representing the Earth's surface by digital elevation models. Such problems are often considered to lie in the field of computer mapping and thus addressed by geographical information systems. The problems include simple identification of local maximum points, visualization by cross-sectional profiles, contour maps and three-dimensional views, consideration of the visual impact of the placement of large buildings and issues arising from reservoir creation. Motion through a virtual landscape can be simulated by an animation facility. This approach has been successful with first year students: the ‘real world’ problems considered are more accessible than many alternatives, and the attraction of using large matrices is retained.     

Comparing conventional and distributed approaches to simulation in a complex supply-chain health system

Decision making in modern supply chains can be extremely daunting due to their complex nature. Discrete-event simulation is a technique that can support decision making by providing what-if analysis and evaluation of quantitative data. However, modelling supply chain systems can result in massively large and complicated models that can take a very long time to run even with today's powerful desktop computers. Distributed simulation has been suggested as a possible solution to this problem, by enabling the use of multiple computers to run models. To investigate this claim, this paper presents experiences in implementing a simulation model with a ‘conventional’ approach and with a distributed approach. This study takes place in a healthcare setting, the supply chain of blood from donor to recipient. The study compares conventional and distributed model execution times of a supply chain model simulated in the simulation package Simul8. The results show that the execution time of the conventional approach increases almost linearly with the size of the system and also the simulation run period. However, the distributed approach to this problem follows a more linear distribution of the execution time in terms of system size and run time and appears to offer a practical alternative. On the basis of this, the paper concludes that distributed simulation can be successfully applied in certain situations.     

Causal study of low stakeholder engagement in healthcare simulation projects

Stakeholder engagement plays a fundamental role in the success of ‘operational research’ initiatives including simulation projects. However, there is little empirical evidence of real engagement in the context of healthcare simulation. This paper principally examines this issue and aims to provide insights into the possible causes. The paper reports on the results of a literature review and 10 field studies within the UK healthcare settings, supplemented with the authors’ experience in order to arrive at an initial list of the causes, which will then be tested through a survey of expert opinions. Twelve primary and 26 secondary causal factors, which received statistically significant level of agreement from the experts, are presented in a fish-bone diagram. The findings indicate that communication gap between simulation and stakeholder groups is the top primary factor contributing the most to the poor stakeholder engagement in healthcare simulation projects, followed by ‘poor management support’, ‘clinician’s high workload’ and ‘failure in producing tangible and quick results’.     

A signal-recovery system: asymptotic properties,and construction of an infinite-volume process

We consider a linear sequence of ‘nodes’, each of which can be in state 0 (‘off’) or 1 (‘on’). Signals from outside are sent to the rightmost node and travel instantaneously as far as possible to the left along nodes which are ‘on’. These nodes are immediately switched off, and become on again after a recovery time. The recovery times are independent exponentially distributed random variables. We present results for finite systems and use some of these results to construct an infinite-volume process (with signals ‘coming from infinity’), which has some peculiar properties. This construction is related to a question by Aldous and we hope that it sheds some light on, and stimulates further investigation of, that question.     

An architecture for integrating logical and physical animations for general-purpose graphical simulation systems

Animation of the logical model is important for debugging the model, and animation of the physical system is important for communicating the results to others. To assure accuracy and consistency between these two animation views of the system, it is necessary to integrate the model building with the production of each animation. This paper describes a new architecture for developing simulation models so that the model created can be used to display both the animation of the system logic and the animation of the physical system.     

Multi-Skilled Workforce Optimisation

This paper describes a problem faced by CS Energy's Swanbank Power Station in the Australian state of Queensland. It involved the personnel scheduling (rostering) of staff with multiple skill levels at the power station. Such a problem can be classified using the six stage construction process proposed by Ernst et al. We assume that the three processes of ‘demand modelling,’ ‘shift starting times’ and ‘task scheduling’ are specified. We are concerned with the essential processes of ‘day off scheduling,’ ‘line of work construction’ and ‘shift assignment to staff’ with requirements to maintain multiple skills. Several other authors have reported results for staff with hierarchical skills while the methods proposed in this paper are for non-hierarchical skill sets. The paper describes a set covering approach to the multi-skilled rostering problem. We propose a number of solution strategies for the set covering approach and give a comparison of the results.     

Soft with a hard centre: discrete-event simulation in facilitation

Discrete event simulation is normally described as a ‘hard’ OR technique. This may not, however, always be the case. An example of a simulation of a user support helpline is described which, it is argued, has many of the traits of a ‘soft’ OR intervention. In particular, the study involved a facilitated discussion around a simulation model about possible improvements to a problem situation. The nature of the intervention is considered from both a methodological and paradigmatic perspective, and conclusions are drawn about where the intervention lies on a ‘hard’ to ‘soft’ continuum. It is argued that ‘soft’ issues need to be subsumed into the prescribed methodology for discrete-event simulation.     

Extinction and permanence of the predator-prey system with general functional response and impulsive control

Traditional approach for modelling the evolution of populations in the predator-prey ecosystem has commonly been undertaken using specific impulsive response function, and this kind of modelling is applicable only for a specific ecosystem under certain environmental situations only. This paper attempts to fill the gap by modelling the predator-prey ecosystem using a ‘generalized’ impulsive response function for the first time. Different from previous research, the present work develops the modelling for an integrated pest management (IPM) especially when the stocking of predator (natural enemy) and the harvesting of prey (pest) occur impulsively and at different instances of time. The paper firstly establishes the sufficient conditions for the local and the global stabilities of prey eradication periodic solution by applying the Floquet theorem of the Impulsive different equation and small amplitude perturbation under a ‘generalized’ impulsive response function. Subsequently the sufficient condition for the permanence of the system is given through the comparison techniques. The corollaries of the theorems that are established by using the ‘general impulsive response function’ under the locally asymptotically stable condition are found to be in excellent agreement with those reported previously. Theoretical results that are obtained in this work is then validated by using a typical impulsive response function (Holling type-II) as an example, and the outcome is shown to be consistent with the previously reported results. Finally, the implication of the developed theories for practical pest management is illustrated through numerical simulation. It is shown that the elimination of either the preys or the pest can be effectively deployed by making use of the theoretical model established in this work. The developed model is capable to predict the population evolutions of the predator-prey ecosystem to accommodate requirements such as: the combinations of the biological control, chemical control, any functional response function, the moderate impulsive period, the harvest rate for the prey and predator parameter and the incremental stocking of the predator parameter.     

An application of probability to combinatorics: a proof of Vandermonde identity

In this paper, we give possible suggestions for a classroom lesson about an application of probability using basic mathematical notions. We will approach to some combinatoric results without using ‘induction’, ‘polynomial identities’ nor ‘generating functions’, and will give a proof of the ‘Vandermonde Identity’ using elementary notions of probability.     

Cross-validation using the t statistic

One application area of regression analysis is simulation where the regression model may explain the relationship between the simulation model's inputs and outputs.However, whether or not the regression model is used in a simulation context, its validity can be tested by comparing the model's forecast to one or more new observations not used in the estimation of the model's parameters. The familiar Student or t statistic is proposed for this comparison, combined with a Bonferroni approach accounting for the presence of multiple, dependent validation observations.A ‘trick’ is used to obtain as many validation observations as possible. This trick is also known as cross-validation.Several Monte Carlo experiments are performed to study the α and β errors of the proposed validation procedure. The experimental results suggest that the procedure is worthwhile.     

A generalized activity network model

In recent years activity networks for projects with both random and deterministic alternative outcomes in key nodes have been considered. The developed control algorithm chooses an optimal outcome direction at every deterministic alternative node which is reached in the course of the project's realization. At each routine decision-making node, the algorithm singles out all the subnetworks (the so-called joint variants) which correspond to all possible outcomes from that node. Decision-making results in determining the optimal joint variant and following the optimal direction up to the next decision-making node. However, such models cover a limited class of alternative networks, namely, only fully-divisible networks which can be subdivided into nonintersecting fragments. In this paper, a more generalized activity network is considered. The model can be applied to a broader spectrum of R&D projects and can be used for all types of alternative networks, for example, for non-divisible networks comprising nodes with simultaneously ‘must follow’, random ‘exclusive OR’ and deterministic ‘exclusive or’ emitters. The branching activities of the third type refer to decision-making outcomes; choosing the optimal outcome is the sole prerogative of the project's management. Such a model is a more universal activity network; we will call it GAAN—Generalized Alternative Activity Network. The problem is to determine the joint variant optimizing the mean value of the objective function subject to restricted mean values of several other criteria. We will prove that such a problem is a NP-complete one. Thus, in general, the exact solution of the problem may be obtained only by looking through all the joint variants on the basis of their proper enumeration. To enumerate the joint variants we will use the lexicographical method in combination with some techniques of discrete optimization. A numerical example will be presented. Various application areas are considered.     

A stochastic fluid model for an ad hoc mobile network

In conventional mobile telephone networks, users communicate directly with a base station, via which their call is transferred to the recipient. In an ad hoc mobile network, there is no base-station infrastructure and users need to communicate between themselves, either directly if they are close enough, or via transit nodes if they are not. A number of interesting questions immediately arise in the modeling of ad hoc mobile networks. One that has received attention in the literature concerns how to encourage users to act as transit nodes for calls that they are not partaking in. Solutions to this problem have involved each user maintaining a ‘credit balance’ which is increased by forwarding transit calls and decreased by transmitting one’s own calls. A second question concerns the ‘amount of resource’ that a network needs in order to be able to operate with a reasonable quality of service. We shall consider this question by modeling each user’s battery energy and credit balance as fluids, the rate of increase or decrease of which is modulated by the network occupancy. This results in a network of stochastic fluid models, each modulated by the same background process. In this paper, we shall assume that there is no bound on the energy or the credit that a user’s handset can accumulate. Using this model, we can calculate the critical rates of recharge that are necessary and sufficient to guarantee that no calls are lost. For recharge rates less than the critical values, we propose a reduced-load approach to the analysis of the network.     

Stochastic Visual Interactive Simulation Models

Many writers and practitioners have mentioned the difficulties that result from randomness in visual interactive simulation or animated simulation modelling. This paper discusses the use of VIS to model transient system behaviour, and proposes some approaches to stochastic VIS modelling which may be helpful in overcoming the difficulties.     

Tactical design of rail freight networks. Part II: Local search methods with statistical analysis

This paper deals with the statistical study of the local search methods which we used in Part I of this work. In that part, a tactical planning model of the rail freight transportation was defined as a network design model. Different local search methods have been used to solve it: Simulated Annealing, Tabu Search and a ‘Descent’ method. The solution and method convergence depends on the initial feasible solution and the convexity of the feasible region, so the comparison among them will be made with the help of statistical theory. Assuming the hypothesis that the distribution of local minima can be represented by the Weibull distribution, it is possible to obtain an approach to the global minimum and a confidence interval of this. The global minimum estimation has been used to compare the heuristic methods and the parameters for a given heuristic, and to obtain a stopping criterion.