Evaluating the effect of gap size in a single function mathematical programming model for the three-group classification problem

This study examines the impact that the size of the classification gap can have on the classificatory performance of a mathematical programming based discriminant model. In mathematical programming based models that project the discriminant scores onto a line, the discriminant score of an observation may fall into the gap between adjacent group intervals; thus there is no clear cut way to determine the group in which the observation should be classified. We examine a procedure that we refer to as the split gap approach. The split gap approach is defined as a strategy of estimating the performance of a mathematical programming based model using a nonzero gap size to separate group intervals and then splitting the gap between adjacent group intervals to classify future observations. Studies that propose models with a classification gap generally do not assess the effect of the gap on the performance of the model. This paper investigates this effect. A theoretical assessment and a Monte Carlo simulation are used to determine the impact of different gap sizes on a mixed integer programming model using a single function classification model for the three-group case.     

Order selection optimization in hybrid make-to-order and make-to-stock markets

The order selection process for firms operating in markets characterized by standard products as well as strong product customization, is directly tied to the customer and to the associated production costs. This order selection process must be inter-functional with marketing and manufacturing in deciding which orders to accept, specially since the selection criteria used by marketing and manufacturing tend to differ. This paper develops a methodology/mathematical programming model for improving this coordination through an optimal selection of sales orders, such that the total financial contribution of selected orders is maximized. Based on an actual case study in the pigment manufacturing industry, the methodology provides for a user interface that addresses both the manufacturing and marketing department. More importantly, such a marketing/production coordination allows for improved performance in increasingly segmented (customized) markets, while continuing standard product lines as well.     

Parallel machine scheduling with a learning effect

The phenomenon of ‘learning’ has been extensively studied in many different areas of Operational Research. However, the ‘learning effect’ of the producer/processor has rarely been studied in the general context of production scheduling, and has never been investigated in multi-machine scheduling settings. We focus in this paper on flow-time minimization on parallel identical machines. We show that this problem has a polynomial time solution, although the computational effort required is much larger than the effort required for solving the classical version of the problem.     

Lower bounding schemes for flowshops with blocking in-process

While there is a considerable amount of research that deals with a flowshop with no storage constraints, few works have addressed the flowshop with blocking in-process. Scheduling problems with blocking arise in serial manufacturing processes where no intermediate buffer storage is available. This paper proposes a lower bound, which exploits the occurrence of blocking, on the total tardiness of the jobs. Its efficiency is evaluated using a branch-and-bound algorithm on several problems. A lower bound on the makespan is also derived and computational tests are presented.     

Mixing methodologies for information systems development and strategy: A higher education case study

Although informed approaches from an interpretivist perspective have been widely promoted over the last two decades information systems development is largely informed by a functionalist perspective, into which human-centred or interpretivist issues are incorporated as they are seen to be required. By treating such developments as critically informed social systems, this paper offers an alternative viewpoint. Firstly, a theoretical justification for such an approach is offered, drawing on developments in Critical Management Science, themselves based on a strand of Critical Social Theory. Secondly, an action research-based intervention is detailed, demonstrating the practical applicability of such an approach, an applicability that has hitherto been questioned. The outcome is a synthesised approach to operational and strategic information systems development, within a critical framework, which, it is argued, offers a greater potential for success than the currently promoted approaches.     

A simulation model of the spread of Hepatitis C within a closed cohort

Many of the epidemics that have been given much publicity in recent years such as AIDS and hepatitis C, are caused by blood borne viruses. Most of these diseases cause long term illnesses and can often be fatal. Apart from the loss of life, the disease phase also makes considerable demands on the health system. As these viruses are spread through direct contact between individuals, changing the factors that contribute to their transmission may be useful in controlling the epidemics. This paper presents a simulation model of the spread of blood borne viruses that can be used to evaluate the effects of such influences. The model is applied to the spread of the hepatitis C virus and is validated using published results from a cohort study of injecting drug users.     

A New Heuristic for a Single Machine Scheduling Problem with Set-up Times

This paper examines the problem of scheduling jobs on a single machine with set-up times. The jobs are divided into mutually exclusive classes and a set-up task is required when processing switches from a job of one class to a job of another class. The set-up times are assumed to be sequence independent. A number of necessary conditions for a schedule to minimize mean flow time have previously been stated, but do not uniquely define the optimal solution, and the problem is apparently NP-complete. We propose a new polynomial-time heuristic, based on these conditions, and compare its performance with some existing heuristics.     

Solving the Generalized Machine Assignment Problem in Group Technology

Many existing solution methodologies for machine assignment problems in group technology do not consider factors such as part demand, operation sequence and cost of intercellular moves. We formulate a 0-1 quadratic programming model that takes into account these factors in machine assignment. Two approaches are proposed to solve this problem. The first is an A*-based approach that generates optimal solutions. The second is a heuristic approach developed to solve problems with large number of machines and/or parts. The heuristic approach is shown to be efficient in producing good solutions in a computational study.     

The Gravitational Deflection of Light in f(R)-Gravity

Gravitation deflects light, which has been confirmed by a large number of observation data. f(R)-gravity is modification of Einstein’s gravity. According to the field equations obtained by the action of the f(R) form, a similar Schwarzschild metric is obtained. According to the condition that four-dimension momenta of the photon return to zero and conservation of covariant momenta, we obtain an equation of photon motion in a specific form of f(R)-gravity. We solve the equation to get gravitational deflection angle of light that grazes surface of sun and the calculation result is consistent with the experimental observation data.