A hybrid model of mathematics support for science students emphasizing basic skills and discipline relevance

The problem of students entering university lacking basic mathematical skills is a critical issue in the Australian higher-education sector and relevant globally. The Maths Skills programme at La Trobe University has been developed to address under preparation in the first-year science cohort in the absence of an institutional mathematics support centre. The programme was delivered through first-year science and statistics subjects with large enrolments and focused on basic mathematical skills relevant to each science discipline. The programme offered a new approach to the traditional mathematical support centre or class. It was designed through close collaboration between science subject coordinators and the project leader, a mathematician, and includes resources relevant to science and mathematics questions written in context. Evaluation of the programme showed it improved the confidence of the participating students who found it helpful and relevant. The programme was delivered through three learning modes to allow students to select activities most suitable for them, which was appreciated by students. Mathematics skills appeared to increase following completion of the programme and student participation in the programme correlated positively and highly with academic grades in their relevant science subjects. This programme offers an alternative model for mathematics support tailored to science disciplines.     

The Australian National Bushfire model project

The National Bushfire Research Unit has developed a personal computer based model to act as a shell for a decision support system for bushfire management. To date the fire spread module has been developed, and there is a continuing programme to incorporate expert systems. The model is designed for real-time operation. Inputs to the model combine a geographic information system (GIS) with real-time data acquisition and data assimilation through modem connections to telephone lines. Outputs are graphical and allow the fire-front position, which is generated using Huygens' principle, to be examined at any desired scale.     

A Study of a Renal Unit

An improved simulation model for predicting future resource use in a Region with haemodialysis facilities and a vigorous transplant programme for patients with chronic renal failure has been developed. This new model differs from its predecessors in incorporating a procedure to match patients with kidneys, an important component of the actual system. It was used in a Region with a large number of dialysis patients and predicted that this number would gradually fall and, in due course, the number of patients on the transplant waiting list would stabilise. The number of permanent dialysis patients and patients with functioning transplanted kidneys would continually increase in number. It is also shown how the model could be used to predict the Regional costs of a dialysis/transplant programme.     

A Note on Chance-Constrained Programming

A stochastic linear programme with chance constraints is considered. By allowing for the possibility of sampling, a so-called dynamic statistical decision model is developed, and the existence of an optimal decision rule is shown under appropriate continuity and compactness assumptions.     

Optimisation of road vehicle passive suspension systems. Part 1. Optimisation algorithm and vehicle model

Numerous problems have in the past been experienced during the development of military vehicle suspension systems. In order to solve some of these problems a two-dimensional multi-body vehicle dynamics simulation model has been developed for computer implementation. This model is linked to a mathematical optimisation algorithm in order to enable the optimisation of vehicle design parameters through the minimisation of a well defined objective function. In part 1 of this paper the concept of multi-disciplinary design optimisation is discussed. This is followed by the presentation of the up to six degrees of freedom vehicle model developed for this study, and a discussion of the specific gradient-based optimisation algorithm selected for the optimisation. In particular the derivation of the set of second-order differential equations, describing the acceleration of the different solid bodies of the vehicle model, is presented. In order to perform the optimisation of the non-linear suspension component characteristics, a six piece-wise continuous and linear approximation is used which is also described in this paper. Part 2 of this study will outline the simulation programme and the qualification of the programme. It will also present a typical case study where the proposed optimisation methodology is applied to improve the damper characteristics of a specific vehicle.     

Optimisation of road vehicle passive suspension systems. Part 2. Qualification and case study

As an aid during the concept design phase, the two-dimensional vehicle simulation programme Vehsim2d has been developed (see part 1 of this paper for the vehicle model). The leap-frog optimisation algorithm for constrained problems (LFOPC) has been linked to the multi-body dynamics simulation code (Vehsim2d) to enable the computationally economic optimisation of certain vehicle and suspension design variables. This paper describes the simulation programme, the qualification of the programme, and gives an example of the application of the Vehsim2d/LFOPC system. In particular it is used to optimise the damper characteristics of an existing 22 ton three axle vehicle, over a typical terrain and at a representative speed. By using this system the optimised damper characteristics with respect to ride comfort for the vehicle are computed. The optimum damper characteristics give a 28.5% improvement in the ride comfort of the vehicle over the specified terrain and prescribed speed. Further optimisation runs were performed considering other terrain and different speed values. From these results final damper characteristics for the vehicle are proposed. Using the proposed characteristics, simulations were performed with the more advanced and proven DADS programme. The results show that the damper suggested by the optimisation study is indeed likely to improve the suspension of the vehicle. This study proves that the Vehsim2d/LFOPC vehicle modelling and optimisation system is indeed a valuable tool for a vehicle design team.     

Selection and Scheduling of Advanced Missions for NASA Using 0-1 Integer Linear Programming

A 0-1 integer linear programme for the selection and scheduling of US National Aeronautics and Space Administration (NASA) missions over a long planning horizon is presented. This model was formulated to allow a higher-level user-interaction with an advanced missions database currently being developed. The model implicitly considers the multi-objective nature of the problem, which results from the desire to maximize benefits in several categories as well as from the desire to minimize cost. In addition, the model allows the planner much flexibility in the selection process. This is accomplished by allowing the planner the ability to specify long- or short-term budget constraints, precursor/follow-on mission requirements, or any number of other idiosyncratic constraints which might be of importance in the decision process. Small example problems are solved in order to illustrate the approach, and areas for further research are discussed.     

The impact of loyalty and promotion effects on retention rate

Researching customer retention rates is made difficult because of the lack of suitable systems with which to measure it. From a first-order Markov brand-switching model, serial equations are derived to estimate the retention rate using market share and loyalty. To explore the impact of loyalty and promotion programme on retention rate, data from five leading brands for three product categories were obtained to fit the developed model. Findings suggest that: (1) when the loyalty effect remains unchanged over a period of time, the greater the effect of a promotion programme, the greater the retention rate; (2) when the promotion effects among brands are similar, the retention rate varies depending on level of loyalty; and (3) when the proportion of loyal customers is high, the proportion of potential switchers affected by promotion programmes is low. In this case, the impact of a promotion programme on the retention rate is not significant. This model successfully demonstrates how the Markov brand-switching model can be employed to estimate a measure of retention rate from consumer panel data as well as to better understand how promotion affects loyalty, switching behaviour, and retention rate.     

Model and Situation Specific O.R. Methods: Risk Engineering Reliability Analysis of an L.N.G. Facility

A decision situation and model-specific O.R. method developed for reliability analysis of an Arctic liquid natural gas facility is outlined. It was developed by modifying a decision situation and model-specific O.R. method developed earlier for time (schedule or programme) risk analysis of offshore North Sea projects. The role and value of such methods is discussed in relation to general O.R. methods and specific techniques like C.P.M./PERT.     

A chance constraints goal programming model for the advertising planning problem

This paper presents a model which has been designed to decide the number of advertisement in different advertising media and the optimal allocation of the budget assigned to the different media. The main objective of this problem is to maximize the reach to the desired section of people for different media within their maximum allowable budget without violating the max and min number of advertisement goals. The media have been considered as different newspapers and different channels in Televisions. Here in this article the model has been formulated in such a way that the advertisement should reach to those who are suitable for the product instead of going to those section who are not considered suitable for the product as well. A chance constrained goal programming model has been designed after considering the parameter corresponding to reach for different media as random variables. The random variables in this case has been considered as values which have known mean and standard deviations. A case for an upcoming institution who are interested to advertise for its two years Post Graduate Diploma in Management (PGDM) programme to the different newspapers and television channels has been designed to illustrate the solution methodology.     

Determination of an Optimal Forecast Model for Ambulance Demand Using Goal Programming

A multistep approach to determining the optimal parameters of an exponential smoothing model was used to forecast emergency medical service (E.M.S.) demand for four counties of South Carolina. Daily emergency and routine (non-emergency) demand data were obtained and forecast statistics generated for each county sampled, using Winters' exponential smoothing model. A goal programme was formulated to combine forecast results for emergency calls with routine call forecasts. The goal programme gave a higher priority to accurate forecasting of emergency demand. The forecast model generated implicitly weights demand by severity and provides a reliable estimate of demand overall. The optimal parameter values for the smoothing model were obtained by minimizing the objective function value of the goal programming problem. The parameter values obtained were used to forecast demand for E.M.S. in the selected counties. The results of the model were compared to those using a multiple linear regression model and a single-objective-based exponential smoothing model for 2 months of data. When compared with two single-objective forecast models, the multiple-objective approach yielded more accurate forecasts and, therefore, was more cost-effective for the planner. The model presents and demonstrates a theoretical approach to improving the accuracy of ambulance demand forecasts. The possible impact of this approach on planning efficiency is discussed.     

LP modelling of the finishing hot rolling programme for low carbon steel coils

In this paper a mathematical model was developed to optimize the finishing rolling of hot rolled coils by increasing the productivity of the rolling programme, to help achieve the required level of quality assurance and to facilitate production planning and control in the hot rolling mill. A brief account of the technological and planning aspects of the hot rolling processes and mills relevant to strip steel is given. Linear (mixed integer) programming is used to formulate the objective function and the various types of constraints of the model. The model takes into consideration, the general aspects pertinent to hot rolling of low carbon steel and the characteristics of the hot rolling mills as stipulated by the operational codes and guidelines of the relevant establishments. Owing to the flexibility offered by linear programming the model can incorporate any modifications and/or additional requirements, if any, in case of other types of steel and/or other types of mills. The full modelling of the problem required the incorporation of some zero/one variable constraints. Owing to the complexity involved and the need to keep the model as simple as possible, it was decided to exclude these constraints and deal with them externally. HYPER LINDO PC was used to solve the programme. Using available data, in the case under consideration the model showed astonishing results in achieving the objectives. Taking into account the effect on the overall productivity as well as quality improvement, the investigation showed that a net improvement in conforming output to the effect of around 43%, could have been obtained had the model been used in the case under consideration.     

Periodic review (<Emphasis Type="Italic">s</Emphasis>, <Emphasis Type="Italic">S</Emphasis>) inventory model with permissible delay in payments

This paper investigates the effect of permissible delay in payments on ordering policies in a periodic review (s, S) inventory model with stochastic demand. A new mathematical model is developed, which is an extension to that of Veinott and Wagner (Mngt Sci 1965; 11: 525) who applied renewal theory and stationary probabilistic analysis to determine the equivalent average cost per review period. The performance of the model is validated using a custom-built simulation programme. In addition, two distribution-free heuristic methods of reasonable accuracy develop approximate optimal policies for practical purposes based only on the mean and the standard deviation of the demand. Numerical examples are presented with results discussed.     

The Efficient Allocation of Private Contractors to Public Works

A large, publicly owned corporation has a yearly problem of allocating work to private contractors. The current heuristic procedure used to do this economically on a minicomputer is described. This quick procedure generally does not lead to an optimal solution. The formulation and solution of the problem as an optimization model (an integer programme) is then described. It is then pointed out that this model can be regarded as a minimum cost network flow model showing the optimization problem to be much easier than it at first appeared. Regarding the problem in this manner has the advantage of (i) showing it is possible to optimize very quickly on a minicomputer; (ii) demonstrating that meaningful shadow prices can be derived.     

Analysing the effectiveness of <Emphasis Type="Italic">Chlamydia</Emphasis> screening

Chlamydia is a highly prevalent sexually transmitted infection which is normally asymptomatic. Chlamydia is a major public health concern since it is one of the biggest causes of infertility in the UK. A screening programme has been proposed and here we analyse its potential cost-effectiveness. Previous modelling analyses for Chlamydia screening have been inadequate at representing the dynamic complexity of the impact. Most notably, the impact on the population prevalence has been overlooked as well as the possibility for an individual to become re-infected after treatment. A system dynamics model was built using the array facility in the ithink software to represent a heterogeneous population. This population was disaggregated along two dimensions: age and sexual activity levels. Results suggest that the proposed screening programme would prevent significant numbers of infertility cases annually. Additionally, it could be paying for itself after about four years and recouping the initial outlay after about twelve years.     

The training institution efficiency of the semiconductor institute programme in Taiwan—application of spatiotemporal ICA with DEA approach

Despite the fact that Taiwan’s high-tech industry has gradually secured a leading position in the world, enterprises in Taiwan have striven to strengthen their technical advancement by providing employees with various internal or external training programmes. These institutional training programmes are designed to sustain competitive advantage, enhance the quality of manpower and improve operational efficiency. Much literature assesses the efficiency of an internal training programme that is initiated by a firm, but only a little literature studies the efficiency of an external training programme that is led by a government. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, the DEA's capability to discriminate efficient decision-making units from inefficient decision-making units requires much improvement (Adler and Yazhemsky). In this paper, a two-stage approach of integrating spatiotemporal independent component analysis (stICA) and DEA is developed for efficiency measurement. stICA is used to search for latent source signals where no relevant signal mixture mechanisms are available; and DEA is used to measure the relative efficiencies of decision-making units (DMUs). We suggest using stICA first to extract the input variables for generating independent components (IC), then selecting the ICs representing the independent sources of input variables, and finally inputting the selected ICs as new variables in the DEA model. To find the effects of environmental variables on the estimated efficiency scores, the Tobit–Bayes (censored) regression is applied. A simulated dataset and the training institution dataset provided by the Semiconductor Institute in Taiwan is used for analysis. The empirical result shows that the proposed method can not only separate performance differences between the training institutions but also improve the discriminatory capability of the DEA's efficiency measurement. The study results can serve as a reference for training institutions wishing to enhance their training efficiency.     

Applying GIS and Combinatorial Optimization to Fiber Deployment Plans

A decision-support system for the Fiber Deployment Plan problem is developed for the telephone cable network design in the telecommunications industry. The system employs a Geographic Information System (GIS) and uses combinatorial optimization techniques as its components. A mathematical combinatorial optimization model is formulated for the problem and a heuristic solution procedure is developed for the model. A GIS within the ESRI Arc/INFO and ArcView environment is used to provide data needed to build the mathematical combinatorial optimization model and to furnish an interface between the users and computers in data input and in solution result display. Combinatorial optimization techniques are used in the heuristic solution procedure to find good solutions for the optimization model. The developed decision-support system has been used to real life problems and has resulted in tremendous improvements in the telephone cable network design process. The user is completely satisfied with the performance of the system.