Markovian bulk-arriving queues with state-dependent control at idle time

This paper considers a Markovian bulk-arriving queue modified to allow both mass arrivals when the queue is idle and mass departures which allow for the possibility of removing the entire workload. Properties of queues which terminate when the server becomes idle are developed first, since these play a key role in later developments. Results for the case of mass arrivals, but no mass annihilation, are then constructed with specific attention being paid to recurrence properties, equilibrium queue-size structure, and waiting-time distribution. A closed-form expression for the expected queue size and its Laplace transform are also established. All of these results are then generalised to allow for the removal of the entire workload, with closed-form expressions being developed for the equilibrium size and waiting-time distributions.

Scaling laws of ambush predator 'waiting' behaviour are tuned to a common ecology

The decisions animals make about how long to wait between activities can determine the success of diverse behaviours such as foraging, group formation or risk avoidance. Remarkably, for diverse animal species, including humans, spontaneous patterns of waiting times show random ‘burstiness’ that appears scale-invariant across a broad set of scales. However, a general theory linking this phenomenon across the animal kingdom currently lacks an ecological basis. Here, we demonstrate from tracking the activities of 15 sympatric predator species (cephalopods, sharks, skates and teleosts) under natural and controlled conditions that bursty waiting times are an intrinsic spontaneous behaviour well approximated by heavy-tailed (power-law) models over data ranges up to four orders of magnitude. Scaling exponents quantifying ratios of frequent short to rare very long waits are species-specific, being determined by traits such as foraging mode (active versus ambush predation), body size and prey preference. A stochastic–deterministic decision model reproduced the empirical waiting time scaling and species-specific exponents, indicating that apparently complex scaling can emerge from simple decisions. Results indicate temporal power-law scaling is a behavioural ‘rule of thumb’ that is tuned to species’ ecological traits, implying a common pattern may have naturally evolved that optimizes move–wait decisions in less predictable natural environments.

Assessing waiting times in the clinical trajectory of patients with lung cancer

Le cancer du poumon a une incidence et une létalité parmi les plus hautes de tous les cancers diagnostiqués au Canada. En considérant la gravité du pronostic et des symptômes de la maladie, l’accès au traitement dans les plus brefs de délais est essentiel. Malgré l’engagement du gouvernement fédéral et les gouvernements provinciaux de réduire les délais de temps d’attente, des balises pour les temps d’attente pour le traitement d’un cancer ne sont toujours pas établis. En outre, le compte-rendu des indicateurs des temps d’attente n’est pas uniforme à travers les provinces. Une des solutions proposées pour la réduction des temps d’attente pour le traitement du cancer est les équipes interdisciplinaires. J’ai complété un audit du programme interdisciplinaire traitant le cancer du poumon à l’Hôpital général juif (l’HGJ) de 2004 à 2007. Les objectifs primaires de l’étude étaient : (1) de faire un audit de la performance de l’équipe interdisciplinaire à l’HGJ en ce qui concerne les temps d’attente pour les intervalles critiques et les sous-groupes de patients ; (2) de comparer les temps d’attente dans la trajectoire clinique des patients traités à l’HGJ avec les balises qui existent ; (3) de déterminer les facteurs associés aux délais plus longs dans cette population. Un objectif secondaire de l’étude était de suggérer des mesures visant à réduire les temps d’attente. Le service clinique à l’HGJ a été évalué selon les balises proposées par le British Thoracic Society, Cancer Care Ontario, et la balise pan-canadienne pour la radiothérapie. Les patients de l’HGJ ont subi un délai médian de 9 jours pour l’intervalle «Ready to treat to first treatment», et un délai médian de 30 jours pour l’intervalle entre le premier contact avec l’hôpital et le premier traitement. Les patients âgés de plus de 65 ans, les patients avec une capacité physique diminuée, et les patients avec un stade de tumeur limité étaient plus à risque d’échouer les balises pour les temps d’attente.

Time and the price impact of a trade

We use Hasbrouck's (1991) vector autoregressive model for prices and trades to empirically test and assess the role played by the waiting time between consecutive transactions in the process of price formation. We find that as the time duration between transactions decreases, the price impact of trades, the speed of price adjustment to trade‐related information, and the positive autocorrelation of signed trades all increase. This suggests that times when markets are most active are times when there is an increased presence of informed traders; we interpret such markets as having reduced liquidity.

A Psychoanalytic Reading of Vladimir and Estragon in Samuel Beckett’s Waiting for Godot

Much has been written about Samuel Beckett’s Waiting for Godot, but as far as I am aware no one has compared the two characters of Vladimir and Estragon in order to analyse what makes Vladimir more willing to wait than Estragon. This essay claims that Vladimir is more willing to wait because he cannot deal with the fact that they might be waiting in vain and he involves himself more in his surrounding than Estragon. It is Vladimir who waits for Godot, not Estragon, and Vladimir believes that Godot will have all the answers. This will be explored by examining four topics, all of which will be dealt with from a psychoanalytical point of view and in relation to waiting. Consciousness in relation to the decision to wait; Uncertainty in relation to the unknown outcome of waiting; Coping mechanisms in relation to ways of dealing with waiting; Ways of waiting in relation to waiting-time and two kinds of waiting-characters.

Waiting times for cataract surgery in ten European countries: an analysis using data from the SHARE survey

AIMS: To assess waiting times for cataract surgery and their acceptance in European countries, and to find explanatory, country-specific health indicators. METHODS: Using data from the survey of health, ageing and retirement in Europe (SHARE), waiting times for cataract surgery of 245 respondents in ten countries were analysed with the help of linear regression. The influence of four country specific health indicators on waiting times was studied by multiple linear regression. The influence of waiting time and country on the wish to have surgery performed earlier was determined through logistic regression. Additional information was obtained for each country from opinion leaders in the field of cataract surgery. RESULTS: Waiting times differed significantly (p<0.001) between the ten analysed European countries. The length of wait was significantly influenced by the total expenditure on health (p<0.01) but not by the other country specific health indicators. The wish to have surgery performed earlier was determined by the length of wait (p<0.001) but not by the country where surgery was performed. CONCLUSION: The length of wait is influenced by the total expenditure on health, but not by the rate of public expenditure on health, by the physician density or by the acute bed density. The wish to have surgery performed earlier depends on the length of wait for surgery and is not influenced by the country.

On Queueinginventory Models – product form solution; reservation, Cancellation and common life time

Queueing theory is the mathematical study of ‘queue’ or ‘waiting lines’ where an item from inventory is provided to the customer on completion of service. A typical queueing system consists of a queue and a server. Customers arrive in the system from outside and join the queue in a certain way. The server picks up customers and serves them according to certain service discipline. Customers leave the system immediately after their service is completed. For queueing systems, queue length, waiting time and busy period are of primary interest to applications. The theory permits the derivation and calculation of several performance measures including the average waiting time in the queue or the system, mean queue length, traffic intensity, the expected number waiting or receiving service, mean busy period, distribution of queue length, and the probability of encountering the system in certain states, such as empty, full, having an available server or having to wait a certain time to be served.

Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion

In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted earliness, the total weighted tardiness and the total weighted waiting time. The criterion takes into account the costs of storing semi-manufactured products in the course of production and ready-made products as well as penalties for not meeting the deadlines stated in the conditions of the contract with customer. To solve the problem, three constructive algorithms and three metaheuristics (based one Tabu Search and Simulated Annealing techniques) are developed and experimentally analyzed. All the proposed algorithms operate on the notion of so-called operation processing order, i.e. the order of operations on each machine. We show that the problem of schedule construction on the base of a given operation processing order can be reduced to the linear programming task. We also propose some approximation algorithm for schedule construction and show the conditions of its optimality.

Evaluating the effect of a patient education brochure on patients’ expectations and satisfaction with emergency department service

Introduction: The purpose of this study was to assess the capacity of a written intervention, in this case a patient information brochure, to improve patient satisfaction during an Emergency Department (ED) visit. For the purpose of measuring the effect of the intervention the ED journey was conceptualised as a series of distinct areas of service comprising waiting time, service by the triage nurse, care from doctors and nurses and information giving Background of study: Research into patient satisfaction has become a widespread activity endorsed by both governments and hospital administrations. The literature on ED patient satisfaction has consistently indicated three primary areas of patient dissatisfaction: waiting time, nursing care and communication. Recent developments in the literature on patient satisfaction studies however have highlighted the relationship between patients. expectations of a service encounter and their consequent assessment of the experience as dissatisfying or satisfying. Disconfirmation theory posits that the degree to which expectations are confirmed will affect subsequent levels of satisfaction. The conceptual framework utilised in this study is Coye.s (2004) model of disconfirmation. Coye while reiterating satisfaction is a consequence of the degree expectations are either confirmed or disconfirmed also posits that expectations can be modified by interventions. Coye.s work conceptualises these interventions as intra encounter experiences (cues) which function to adjust expectations. Coye suggests some cues are unintended and may have a negative impact which also reinforces the value of planned cues intended to meet or exceed consumer expectations. Consequently the brochure can be characterized as a potentially positive cue, encouraging the patient to understand processes and to orient them in what can be a confronting environment. Only a limited number of studies have examined the effect of written interventions within an ED. No studies could be located which have tested the effect of ED interventions using a conceptual framework which relates the effect of the degree to which expectations are confirmed or disconfirmed in terms of satisfaction with services. Method: Two studies were conducted. Study One used qualitative methods to explore patients. expectations of the ED from the perspective of both patients and health care professionals. Study One was used in part to direct the development of the intervention (brochure) in Study Two. The brochure was an intervention designed to modify patients. expectations thus increasing their satisfaction with the provision of ED service. As there was no existing tools to measure ED patients. expectations and satisfaction a new tool was also developed based on the findings and the literature of Study One. Study Two used a non-randomised, quasi-experimental approach using a non-equivalent post-test only comparison group design used to investigate the effect of the patient education brochure (Stommel and Wills, 2004). The brochure was disseminated to one of two study groups (the intervention group). The effect of the brochure was assessed by comparing the data obtained from both the intervention and control group. These two groups consisted of 150 participants each. It was expected that any differences in the relevant domains selected for examination would indicate the effect of the brochure both on expectation and potentially satisfaction. Results: Study One revealed several areas of common ground between patients and nurses in terms of relevant content for the written intervention, including the need for information on the triage system and waiting times. Areas of difference were also found with patients emphasizing communication issues, whereas focus group members expressed concern that patients were often unable to assimilate verbal information. The findings suggested the potential utility of written material to reinforce verbal communication particularly in terms of the triage process and other ED protocols. This material was synthesized within the final version of the written intervention. Overall the results of Study Two indicated no significant differences between the two groups. The intervention group did indicate a significant number of participants who viewed the brochure of having changed their expectations. The effect of the brochure may have been obscured by a lack of parity between the two groups as the control group presented with statistically significantly higher levels of acuity and experienced significantly shorter waiting times. In terms of disconfirmation theory this would suggest expectations that had been met or exceeded. The results confirmed the correlation of expectations with satisfaction. Several domains also indicated age as a significant predictor with older patients tending to score higher satisfaction results. Other significant predictors of satisfaction established were waiting time and care from nurses, reinforcing the combination of efficient service and positive interpersonal experiences as being valued by patients. Conclusions: Information presented in written form appears to benefit a significant number of ED users in terms of orientation and explaining systems and procedures. The degree to which these effects may interact with other dimensions of satisfaction however is likely to be limited. Waiting time and interpersonal behaviours from staff also provide influential cues in determining satisfaction. Written material is likely to be one element in a series of coordinated strategies to improve patient satisfaction during periods of peak demand.

Evaluation on service quality of railway timetable

From the business viewpoint, the railway timetable is a list of the products presented by the railway transportation operators to the customers, specifying the schedules of all the train services on a railway line or network. In order to evaluate the quality of the train service schedules, a number of indices are proposed in this paper. These indices primarily take the passengers’ needs, such as waiting time, transfer time and transport capacity into consideration. Delay rate is usually used in post-evaluation. In this study, we propose to give an evaluation on the probability that the scheduled train services are likely to be delayed and the recovery ability of the timetable after delay has occurred. The evaluation identifies the possible problems in the services, such as excessive waiting time, non-seamless transfer, and high possibility of delay. This paper also discusses the improvement of these problems through certain adjustments on the timetable. The indices for evaluation and the adjustment method on timetable are then applied to a case study on the Hu-Ning-Hang railway in China, followed by the discussions of the merits of the proposed indices for timetable evaluation and possible improvement.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Measuring transit service reliability using data from web-based transit user survey : a case study at Brisbane, Australia

This paper reports an empirical study on measuring transit service reliability using the data from a Web-based passenger survey on a major transit corridor in Brisbane, Australia. After an introduction of transit service reliability measures, the paper presents the results from the case study including study area, data collection, and reliability measures obtained. This includes data exploration of boarding/arrival lateness, in-vehicle time variation, waiting time variation, and headway adherence. Impacts of peak-period effects and separate operation on service reliability are examined. Relationships between transit service characteristics and passenger waiting time are also discussed. A summary of key findings and an agenda of future research are offered in conclusions.

Quantification of particle emission characteristics and development of an emission model for use in transport microenvironments affected by traffic emissions

Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.

Application of operations research techniques to improve efficiency in the emergency department

The main aim of this thesis is to analyse and optimise a public hospital Emergency Department. The Emergency Department (ED) is a complex system with limited resources and a high demand for these resources. Adding to the complexity is the stochastic nature of almost every element and characteristic in the ED. The interaction with other functional areas also complicates the system as these areas have a huge impact on the ED and the ED is powerless to change them. Therefore it is imperative that OR be applied to the ED to improve the performance within the constraints of the system. The main characteristics of the system to optimise included tardiness, adherence to waiting time targets, access block and length of stay. A validated and verified simulation model was built to model the real life system. This enabled detailed analysis of resources and flow without disruption to the actual ED. A wide range of different policies for the ED and a variety of resources were able to be investigated. Of particular interest was the number and type of beds in the ED and also the shift times of physicians. One point worth noting was that neither of these resources work in isolation and for optimisation of the system both resources need to be investigated in tandem. The ED was likened to a flow shop scheduling problem with the patients and beds being synonymous with the jobs and machines typically found in manufacturing problems. This enabled an analytic scheduling approach. Constructive heuristics were developed to reactively schedule the system in real time and these were able to improve the performance of the system. Metaheuristics that optimised the system were also developed and analysed. An innovative hybrid Simulated Annealing and Tabu Search algorithm was developed that out-performed both simulated annealing and tabu search algorithms by combining some of their features. The new algorithm achieves a more optimal solution and does so in a shorter time.

A review of models and model usage scenarios for an airport complex system

Airports represent the epitome of complex systems with multiple stakeholders, multiple jurisdictions and complex interactions between many actors. The large number of existing models that capture different aspects of the airport are a testament to this. However, these existing models do not consider in a systematic sense modelling requirements nor how stakeholders such as airport operators or airlines would make use of these models. This can detrimentally impact on the verification and validation of models and makes the development of extensible and reusable modelling tools difficult. This paper develops from the Concept of Operations (CONOPS) framework a methodology to help structure the review and development of modelling capabilities and usage scenarios. The method is applied to the review of existing airport terminal passenger models. It is found that existing models can be broadly categorised according to four usage scenarios: capacity planning, operational planning and design, security policy and planning, and airport performance review. The models, the performance metrics that they evaluate and their usage scenarios are discussed. It is found that capacity and operational planning models predominantly focus on performance metrics such as waiting time, service time and congestion whereas performance review models attempt to link those to passenger satisfaction outcomes. Security policy models on the other hand focus on probabilistic risk assessment. However, there is an emerging focus on the need to be able to capture trade-offs between multiple criteria such as security and processing time. Based on the CONOPS framework and literature findings, guidance is provided for the development of future airport terminal models.