The Teaching Space Allocation Problem with splitting

A standard problem within universities is that of teaching space allocation which can be thought of as the assignment of rooms and times to various teaching activities. The focus is usually on courses that are expected to fit into one room. However, it can also happen that the course will need to be broken up, or ‘split’, into multiple sections. A lecture might be too large to fit into any one room. Another common example is that of seminars or tutorials. Although hundreds of students may be enrolled on a course, it is often subdivided into particular types and sizes of events dependent on the pedagogic requirements of that particular course. Typically, decisions as to how to split courses need to be made within the context of limited space requirements. Institutions do not have an unlimited number of teaching rooms, and need to effectively use those that they do have. The efficiency of space usage is usually measured by the overall ‘utilisation’ which is basically the fraction of the available seat-hours that are actually used. A multi-objective optimisation problem naturally arises; with a trade-off between satisfying preferences on splitting, a desire to increase utilisation, and also to satisfy other constraints such as those based on event location and timetabling conflicts. In this paper, we explore such trade-offs. The explorations themselves are based on a local search method that attempts to optimise the space utilisation by means of a ‘dynamic splitting’ strategy. The local moves are designed to improve utilisation and satisfy the other constraints, but are also allowed to split, and un-split, courses so as to simultaneously meet the splitting objectives.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.

Threshold effects in the Teaching Space Allocation Problem with Splitting

Universities aim for good “Space Management” so as to use the teaching space efficiently. Part of this task is to assign rooms and time-slots to teaching activities with limited numbers and capacities of lecture theaters, seminar rooms, etc. It is also common that some teaching activities require splitting into multiple events. For example, lectures can be too large to fit in one room or good teaching practice requires that seminars/tutorials are taught in small groups. Then, space management involves decisions on splitting as well as the assignments to rooms and time-slots. These decisions must be made whilst satisfying the pedagogic requirements of the institution and constraints on space resources. The efficiency of such management can be measured by the “utilisation”: the percentage of available seat-hours actually used. In many institutions, the observed utilisation is unacceptably low, and this provides our underlying motivation: to study the factors that affect teaching space utilisation, with the goal of improving it. We give a brief introduction to our work in this area, and then introduce a specific model for splitting. We present experimental results that show threshold phenomena and associated easy-hard-easy patterns of computational difficulty. We discuss why such behaviour is of importance for space management.

Towards Improving the Utilisation of University Teaching Space

There is a perception that teaching space in universities is a rather scarce resource. However, some studies have revealed that in many institutions it is actually chronically under-used. Often, rooms are occupied only half the time, and even when in use they are often only half full. This is usually measured by the ‘utilization’ which is defined as the percentage of available ‘seat-hours’ that are employed. Within real institutions, studies have shown that this utilization can often take values as low as 20–40%. One consequence of such a low level of utilization is that space managers are under pressure to make more efficient use of the available teaching space. However, better management is hampered because there does not appear to be a good understanding within space management (near-term planning) of why this happens. This is accompanied, within space planning (long-term planning) by a lack of experise on how best to accommodate the expected low utilizations. This motivates our two main goals: (i) To understand the factors that drive down utilizations, (ii) To set up methods to provide better space planning. Here, we provide quantitative evidence that constraints arising from timetabling and location requirements easily have the potential to explain the low utilizations seen in reality. Furthermore, on considering the decision question ‘Can this given set of courses all be allocated in the available teaching space?’ we find that the answer depends on the associated utilization in a way that exhibits threshold behaviour: There is a sharp division between regions in which the answer is ‘almost always yes’ and those of ‘almost always no’. Through analysis and understanding of the space of potential solutions, our work suggests that better use of space within universities will come about through an understanding of the effects of timetabling constraints and when it is statistically likely that it will be possible for a set of courses to be allocated to a particular space. The results presented here provide a firm foundation for university managers to take decisions on how space should be managed and planned for more effectively. Our multi-criteria approach and new methodology together provide new insight into the interaction between the course timetabling problem and the crucial issue of space planning.

Reliability Assessment of 3-D Space Frame Structures Applying Stochastic Finite Element Analysis

Throughout design development of satellite structure, stress engineer is usually challenged with randomness in applied loads and material properties. To overcome such problem, a risk-based design is applied which estimates satellite structure probability of failure under static and thermal loads. Determining probability of failure can help to update initially applied factors of safety that were used during structure preliminary design phase. These factors of safety are related to the satellite mission objective. Sensitivity-based analysis is to be implemented in the context of finite element analysis (probabilistic finite element method or stochastic finite element method (SFEM)) to determine the probability of failure for satellite structure or one of its components.

Efficient Architectural Design Space Exploration via Predictive Modeling

Efficiently exploring exponential-size architectural design spaces with many interacting parameters remains an open problem: the sheer number of experiments required renders detailed simulation intractable.We attack this via an automated approach that builds accurate predictive models. We simulate sampled points, using results to teach our models the function describing relationships among design parameters. The models can be queried and are very fast, enabling efficient design tradeoff discovery. We validate our approach via two uniprocessor sensitivity studies, predicting IPC with only 1–2% error. In an experimental study using the approach, training on 1% of a 250-K-point CMP design space allows our models to predict performance with only 4–5% error. Our predictive modeling combines well with techniques that reduce the time taken by each simulation experiment, achieving net time savings of three-four orders of magnitude.

Does the UK Local Finance Improvement Trust (Lift) Initiative Improve Risk Management in Public-Private Procurement?

The UK government introduced the Private Finance Initiative (PFI) and, latterly, the Local Improvement Finance Trust (LIFT) in an attempt to improve public service provision. As a variant of PFI, LIFT seeks to create a framework for the effective provision of primary care facilities. Like conventional PFI procurement, LIFT projects involve long-term contracts, complex multi-party interactions and thus create various risks to public sector clients. This paper investigates the advantages and disadvantages of LIFT with a focus on how this approach facilitates or impedes risk management from the public sector client perspective. Our paper concludes that LIFT has a potential for creating additional problems, including the further reduction of public sector control, conflicts of interest, the inappropriate use of enabling funds, and higher than market rental costs affecting the uptake of space in the buildings by local health care providers. However, there is also evidence that LIFT has facilitated new investment and that Primary Care Trusts (PCTs) have themselves started addressing some of the weaknesses of this procurement format through the bundling of projects and other forms of regional co-operation.

An Evaluation of the Dual Diagnosis (substance use and mental health )Strategy in the South Eastern Trust Workers and Service Users Perceptions of Dual Diagnosis Issues

In the UK it is estimated that over 33% of psychiatric patients with enduring mental illness have a substance misuse problem, whilst over 50 % of clients currently accessing drug and alcohol services have a mental health problem. Between 2003 and 2013 in Northern Ireland, there were 741 recorded suicides by patients who were in contact with mental health services. Of this number, 68% (n=501) had a history of either alcohol or drug misuse or both, resulting in an average of 46 patient suicides per year associated with dual diagnosis (University of Manchester 2015).
The current evaluation examined staff attitudes towards working with dual diagnosis (co-existing difficulties) issues, staff confidence in working with clients with dual diagnosis, workers’ perceptions of the South Eastern dual diagnosis strategy and service user perspectives of dual diagnosis service provision.
The purpose of the evaluation was to provide evidence regarding the following in accordance with the current dual diagnosis strategy;
Staff understanding of the concept of dual diagnosis,
Staff attitudes towards working with dual diagnosis,
Staff confidence in working with individuals, who present with dual diagnosis,
Service users’ perspectives of SE Trust provision for dual diagnosis.
Staff views on the South Eastern Trust Dual Diagnosis Strategy.

Investigating Fractured Flow from Orthopaedics to Rehabilitation

Patients often spend time as inpatients in hospitals outside their home area because of the need to access specialist services. If there is a need for ongoing care after the need for specialist care has passed, patients are transferred (or ‘repatriated’) back to the inpatient care of a hospital in their local Health and Social Care Trust. The need for bed space in specialist units means that there is pressure for this transition to occur in a timely way. We investigated the flow of patients through a trauma and orthopaedics unit using the 6M Design® framework and Vitals Charts® in order to investigate concerns about delayed repatriation. We found that repatriation was part of a complex system that had interdependent components. There was considerable variation in the number of discharges (to any destination) by day of week, with a reduction on Saturdays and Sundays. Understanding that the pressure for quicker repatriation was really due to high work-in-progress led us to model the effects of strategies to address the high work-in-progress. We found that, because only a small proportion of patients require repatriation, expediting the repatriation process by one day for each patient would only reduce WIP by an average of 1.6 patients. Reducing the average length of stay for all trauma and orthopaedics inpatients by one day would reduce the WIP by 10 patients, which would make a much greater impact on the problem of high bed occupancy. Though the smooth and timely repatriation of patients to rehabilitation units is desirable, it is unlikely that efforts to achieve this will have a substantial impact on the problem of high WIP, so other strategies will be required. We will model the effects of strategies to reduce variation in daily discharges by the day of week in a future essay.