The importance of considering pushback time and arrivals when routing departures on the ground at airports

With the constant increase in air traffic, airports are facing capacity problems. Many airports are increasingly interested in utilising optimisation methods for specific airport processes. However, many such processes do happen in parallel, and maximising the potential benefits will require a complex optimisation model. A model which considers multiple processes simultaneously and the detailed complexities of the processes, rather than using more abstract models. This paper investigates how the arriving aircraft can affect the routing process and whether the pushback process can result into different types of delays. Furthermore, aircraft are routed backwards, starting from the destination in order to be at the runway on time and to respect the departure sequence. After testing our model with and without the arriving aircraft we found that arriving aircraft can indeed produce a lot of delays. Such delays would otherwise pass unnoticed as they result to departing aircraft choose different paths or pushback earlier so they be at the runway on time. Having an accurate model for the pushback process is important in order to understand in depth how the pushback process affects the other processes that happen in parallel. Furthermore, it led to more accurate and realistic model, which may assist the decision making process for ground movement operations and thereby help airports increase their capacity and become more environmentally friendly

The importance of considering pushback time and arrivals when routing departures on the ground at airports

With the constant increase in air traffic, airports are facing capacity problems. Many airports are increasingly interested in utilising optimisation methods for specific airport processes. However, many such processes do happen in parallel, and maximising the potential benefits will require a complex optimisation model. A model which considers multiple processes simultaneously and the detailed complexities of the processes, rather than using more abstract models. This paper investigates how the arriving aircraft can affect the routing process and whether the pushback process can result into different types of delays. Furthermore, aircraft are routed backwards, starting from the destination in order to be at the runway on time and to respect the departure sequence. After testing our model with and without the arriving aircraft we found that arriving aircraft can indeed produce a lot of delays. Such delays would otherwise pass unnoticed as they result to departing aircraft choose different paths or pushback earlier so they be at the runway on time. Having an accurate model for the pushback process is important in order to understand in depth how the pushback process affects the other processes that happen in parallel. Furthermore, it led to more accurate and realistic model, which may assist the decision making process for ground movement operations and thereby help airports increase their capacity and become more environmentally friendly

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

The effects of pushback delays on airport ground movement

With the constant increase in air traffic, airports are facing capacity problems. Optimisation methods for specific airport processes are starting to be increasingly utilised by many large airports. However, many processes do happen in parallel, and maximising the potential benefits will require a more complex optimisation model, which can consider multiple processes simultaneously and take into account the detailed complexities of the processes where necessary, rather than using more abstract models. This paper focuses on one of these complexities, which is usually ignored in ground movement planning; showing the importance of the pushback process in the routing process. It investigates whether taking the pushback process into consideration can result in the prediction of delays that would otherwise pass unnoticed. Having an accurate model for the pushback process is important for this and identifying all of the delays that may occur can lead to more accurate and realistic models that can then be used in the decision making process for ground movement operations. After testing two different routing methods with a more detailed pushback process, we found that many of the delays are not predicted if the pushback process is not explicitly modelled. Having a more precise model, with accurate movements of aircraft is very important for any integrated model and will allow ground movement models to be of use in more reliable integrated decision making systems at airports. Minimising these delays can help airports increase their capacity and become more environmentally friendly

Human performance and strategies while solving an aircraft routing and sequencing problem: an experimental approach

As airport resources are stretched to meet increasing demand for services, effective use of ground infrastructure is increasingly critical for ensuring operational efficiency. Work in operations research has produced algorithms providing airport tower controllers with guidance on optimal timings and sequences for flight arrivals, departures, and ground movement. While such decision support systems have the potential to improve operational efficiency, they may also affect users’ mental workload, situation awareness, and task performance. This work sought to identify performance outcomes and strategies employed by human decision makers during an experimental airport ground movement control task with the goal of identifying opportunities for enhancing user-centered tower control decision support systems. To address this challenge, thirty novice participants solved a set of vehicle routing problems presented in the format of a game representing the airport ground movement task practiced by runway controllers. The games varied across two independent variables, network map layout (representing task complexity) and gameplay objective (representing task flexibility), and verbal protocol, visual protocol, task performance, workload, and task duration were collected as dependent variables. A logistic regression analysis revealed that gameplay objective and task duration significantly affected the likelihood of a participant identifying the optimal solution to a game, with the likelihood of an optimal solution increasing with longer task duration and in the less flexible objective condition. In addition, workload appeared unaffected by either independent variable, but verbal protocols and visual observations indicated that high-performing participants demonstrated a greater degree of planning and situation awareness. Through identifying human behavior during optimization problem solving, the work of tower control can be better understood, which, in turn, provides insights for developing decision support systems for ground movement management

β-adrenergic receptor antagonists and fracture risk : a meta-analysis of selectivity, gender, and site-specific effects

Summary By meta-analysis, the risk of fracture was 15 % lower in patients treated with β-adrenergic blockers compared to controls independent of gender, fracture site, and dose. This might be attributable to β1-selective blockers. Introduction The aim of this study is to determine by meta-analysis whether β-adrenergic blockers (BBs) reduce fracture risk and whether the effect, if demonstrable, is dependent upon selectivity, dose, gender, or fracture site. Methods A literature search was performed in electronic databases MEDLINE, EMBASE, and reference sections of relevant articles to identify eligible studies. Adjusted estimates of fracture risk effect size (ES) were pooled across studies using fixed or random-effects (RE) meta-analysis as appropriate. Dose-related effects were evaluated using meta-regression. To explore the relative efficacy of β1-selective blockers in comparison to nonselective BBs, adjusted indirect comparison was performed. Results A total of 16 studies (7 cohort and 9 case–control studies), involving 1,644,570 subjects, were identified. The risk of any fracture was found to be significantly reduced in subjects receiving BBs as compared to control subjects (16 studies, RE pooled ES = 0.86, 95 % CI 0.78–0.93; I2 = 87 %). In a sensitivity analysis limited to those studies deemed to be most robust, the BB effect to reduce fracture risk was sustained (four studies, pooled ES = 0.79, 95 % CI 0.67–0.94; I2 = 96 %). The risk of a hip fracture was lower in both women and men receiving BBs (women: pooled ES = 0.86, 95 % CI 0.80–0.91; I2 = 1 % and men: pooled ES = 0.80, 95 % CI 0.71–0.90; I2 = 0 %). Similar risk reductions were found for clinical vertebral and forearm fractures, although statistical significance was not reached. The reduction in risk did not appear to be dose-related (test for a linear trend p value 0.150). Using adjusted indirect comparisons, it was estimated that β1-selective agents were significantly more effective than nonselective BBs in reducing the risk of any fracture (six studies, β1-selective blockers vs. nonselective BBs: RE pooled ES = 0.82, 95 % CI = 0.69–0.97). Conclusions The findings suggest that the risk of fracture is approximately 15 % lower in patients treated with BBs compared to controls independent of gender, fracture site, and dose. This risk reduction might be associated with the effects of β1-selective blockers