Search

In previous work, we proposed and studied a new dynamic formulation of the Location-allocation (LA) problem called the Dynamic-Customer Location-allocation (DC-LA) problem. DC-LA is based on the idea of changes in customer distribution over a defined period, and these changes have to be taken into account when establishing facilities to service changing customers distributions. This necessitated a dynamic stochastic evaluation function Which came with a high computational cost due to a large number of simulations required in the evaluation process.In this paper, we investigate the use of racing, an approach used in model selection, to reduce the high computational cost by employing the minimum number of simulations for solution selection. Our adaptation of racing uses the Friedman test to compare solutions statistically. Racing allows simulations to be performed iteratively, ensuring that the minimum number of simulations is performed to detect a statistical difference.We present experiments using Population-Based Incremental Learning (PBIL) to explore the savings achievable from using racing in this way. Our results show that racing achieves improved cost savings over the dynamic stochastic evaluation function. We also observed that on average, the computational cost of racing was about 4.5 times loWer than the computational cost of the full dynamic stochastic evaluation.

Part 1 Therapeutic themes: containing care making sense of symbolic communication whose feelings am I feeling? using the concept of projective identification exploring the language - a practice-based glossary support and supervision understanding the research. Part 2 Direct work: assessing the emotional needs of children and young people - using a need assessment programme using a therapeutic model of thought and practice healing play adolescence - a time of transitions the difficulties of working with violence in young people working with sexually abused children in the context of the family throughcare - supporting young people as they make the transition from residential care to the wider community. Part 3 The carer, the family, the group and the organization: isolated and beleaguered staff in impossible situations "residential staff should not touch children" - can we really look after children this way? adolescence and the struggle to feel real the re-enactment of family dynamics in child care working with unconscious dynamics in groups coping with anxiety and complexity - a model of management.

In this paper, we introduce a new stochastic Location-Allocation Problem which assumes the movement of customers over time. We call this new problem Dynamic Customer Location-Allocation Problem (DC-LAP). The problem is based on the idea that customers will change locations over a defined horizon and these changes have to be taken into account when establishing facilities to service customers demands. We generate 1440 problem instances by varying the problem parameters of movement rate which determines the possible number of times a customer will change locations over the defined period, the number of facilities and the number of customers. We propose to analyse the characteristics of the instances generated by testing a search algorithm using the stochastic dynamic evaluation (based on the replication of customer movement scenarios) and a deterministic static evaluation (based on the assumption that customer will not move over time). We show that the dynamic approach obtains globally better results, but the performances are highly related to the parameters of the problem. Moreover, the dynamic approach involves a significantly high computational overhead.

The Uncapacitated Location-Allocation problem (ULAP) is a major optimisation problem concerning the determination of the optimal location of facilities and the allocation of demand to them. In this paper, we present two novel problem variants of Non-Linear ULAP motivated by a real-world problem from the telecommunication industry: Uncapacitated Location-Allocation Resilience problem (ULARP) and Uncapacitated Location-Allocation Resilience problem with Restrictions (ULARPR). Problem sizes ranging from 16 to 100 facilities by 50 to 10000 demand points are considered. To solve the problems, we explore the components and configurations of four Genetic Algorithms [1]–[3] and [4] selected from the ULAP literature. We aim to understand the contribution each choice makes to the GA performance and so hope to design an Optimal GA configuration for the novel problems. We also conduct comparative experiments with Population-Based Incremental Learning (PBIL) Algorithm on ULAP. We show the effectiveness of PBIL and GA with parameter set: random and heuristic initialisation, tournament and fined_grained tournament selection, uniform crossover and bitflip mutation in solving the proposed problems.

In this paper, we introduce a dynamic variant of the Location-Allocation problem: Dynamic Location-Allocation Problem (DULAP). DULAP involves the location of facilities to service a set of customer demands over a defined horizon. To evaluate a solution to DULAP, we propose two holistic metric approaches: Static and Dynamic Approach. In the static approach, a solution is evaluated with the assumption that customer locations and demand remain constant over a defined horizon. In the dynamic approach, the assumption is made that customer demand, and demographic pattern may change over the defined horizon. We introduce a stochastic model to simulate customer population and distribution over time. We use a Genetic Algorithm and Population-Based Incremental Learning algorithm used in previous work to find robust and satisfactory solutions to DULAP. Results show the dynamic approach of evaluating a solution finds good and robust solutions.

Virtual reality technology is argued to be suitable to the simulation study of mass evacuation behavior, because of the practical and ethical constraints in researching this field. This article describes three studies in which a new virtual reality paradigm was used, in which participants had to escape from a burning underground rail station. Study 1 was carried out in an immersion laboratory and demonstrated that collective identification in the crowd was enhanced by the (shared) threat embodied in emergency itself. In Study 2, high-identification participants were more helpful and pushed less than did low-identification participants. In Study 3, identification and group size were experimentally manipulated, and similar results were obtained. These results support a hypothesis according to which (emergent) collective identity motivates solidarity with strangers. It is concluded that the virtual reality technology developed here represents a promising start, although more can be done to embed it in a traditional psychology laboratory setting.

Summary Pressure-rate deconvolution provides equivalent representation of variable-rate well-test data in the form of characteristic constant rate drawdown system response. Deconvolution allows one to develop additional insights into pressure transient behavior and extract more information from well-test data than is possible by using conventional analysis methods. In some cases, it is possible to interpret the same test data in terms of larger radius of investigation. There are a number of specific issues of which one has to be aware when using pressure-rate deconvolution. In this paper, we identify and discuss these issues and provide practical considerations and recommendations on how to produce correct deconvolution results. We also demonstrate reliable use of deconvolution on a number of real test examples.

Pressure-rate deconvolution provides equivalent representation of variable-rate well test data in the form of characteristic constant rate drawdown system response. Deconvolution allows one to develop additional insights into pressure transient behavior and extract more information from well test data than is possible by using conventional analysis methods. In some cases it is possible to interpret the same test data in terms of larger radius of investigation. There are a number of specific issues one has to be aware when using pressure-rate deconvolution. In this paper, we identify and discuss these issues, and provide practical considerations and recommendations on how to produce correct deconvolution results. We also demonstrate reliable use of deconvolution on a number of real test examples.

The mixing properties of aluminosilicate melts in the systems NaAlSi4O10-KAlSi4O10 and NaAlSi5O12-KAlSi5O12 have been determined by measuring the compositions of their saturated vapours by Knudsen cell mass spectrometry. The melts mix very close to ideally over the whole composition range in agreement with theoretical models and the predictions of our previous work.

International audience; In this work, we performed computer simulations of halothane embedded in a fully hydrated dimyristoylphosphatidylcholine (DMPC) membrane. Since the action of general anaesthetics was known to be pressure dependent, we carried out the simulations performed under physiological conditions and also at elevated pressures (i.e., 2 × 10 7 Pa and 4 × 10 7 Pa). The results clearly show that at high pressures the halothane molecules tend to cluster together. Based on these results, we propose a possible mechanism for the pressure reversal of anaesthesia.