Exploration of the ordering for a sequential airport ground movement algorithm

Guiding aircraft around the airport's surface while ensuring conflict-free routings is an important problem at airports. Sequential routing and scheduling algorithms can be advantageous for providing fast online solutions for decision support systems to help controllers. However, the effectiveness of such algorithms can depend upon the sequence of consideration of the aircraft, which is often chosen to be first-come-first-served. This research analyses the effects of different heuristics to find better sequences. Results are presented, utilising real data from Zurich Airport. These show that sophisticated heuristics can substantially improve the solution with comparatively little additional computational time. Furthermore, one approach aims to modify relatively few existing routes as it progresses, in order to minimise the workload of the controllers in communicating changes in an online environment

Constrained portfolio optimisation: the state-of-the-art Markowitz models

This paper studies the state-of-art constrained portfolio optimisation models, using exact solver to identify the optimal solutions or lower bound for the benchmark instances at the OR-library with extended constraints. The effects of pre-assignment, round-lot, and class constraints based on the quantity and cardinality constrained Markowitz model are firstly investigated to gain insights of increased problem difficulty, followed by the analysis of various constraint settings including those mostly studied in the literature. The study aims to provide useful guidance for future investigations in computational algorithm

Adaptation Strategies followed by the Rice Growers to Mitigate the Impact of Climate Change

The study was conducted in Orathanadu block of Thanjavur district in Tamil Nadu. Proportionate random sampling was employed to select the sample. It was observed that the variables viz., educational status and fatalism showed positive significant correlation at one per cent level of probability whereas awareness on climate change showed negative correlation. Variables like annual income, extension agency contact and awareness on crop insurance showed negative correlation at five per cent level of probabilit

A brief overview on an air transportation system (ATS)

The worldwide Air Transport System (ATS) has a huge impact on the global economy and is expected to grow annually in size and operational costs. This impact has led the ATS to attract the attention of researchers worldwide. This article aims to provide an operational insight into the ATS by discussing the major stages of the flight planning process, which is commonly known as airline scheduling, and elaborates how the traversal of flights takes place in the ATS after the filing of flight plan. The reader will also see references to other research which can provide further information, in the hope that this article can be of use to those who are beginning to look into this area

Analysis of objectives relationships in multiobjective problems using trade-off region maps

Understanding the relationships between objectives in many-objective optimisation problems is desirable in order to develop more effective algorithms. We propose a techniquefor the analysis and visualisation of complex relationships between many (three or more) objectives. This technique looks at conflicting, harmonious and independent objectives relationships from different perspectives. To do that, it uses correlation, trade-off regions maps and scatter-plots in a four step approach. We apply the proposed technique to a set of instances of the well-known multiobjective multidimensional knapsack problem. The experimental results show that with the proposed technique we can identify local and complex relationships between objectives, trade-offs not derived from pairwise relationships, gaps in the fitness landscape, and regions of interest. Such information can be used to tailor the development of algorithms

Aspartame in conjunction with carbohydrate reduces insulin levels during endurance exercise

Gold OAAs most sport drinks contain some form of non-nutritive sweetener (e.g. aspartame), and with the variation in blood glucose regulation and insulin secretion reportedly associated with aspartame, a further understanding of the effects on insulin and blood glucose regulation during exercise is warranted. Therefore, the aim of this preliminary study was to profile the insulin and blood glucose responses in healthy individuals after aspartame and carbohydrate ingestion during rest and exercise. Each participant completed four trials under the same conditions (45 min rest + 60 min self-paced intense exercise) differing only in their fluid intake: 1) carbohydrate (2% maltodextrin and 5% sucrose (C)); 2) 0.04% aspartame with 2% maltodextrin and 5% sucrose (CA)); 3) water (W); and 4) aspartame (0.04% aspartame with 2% maltodextrin (A)). Insulin levels dropped significantly for CA versus C alone (43%) between pre-exercise and 30 min, while W and A insulin levels did not differ between these time points. Aspartame with carbohydrate significantly lowered insulin levels during exercise versus carbohydrate alone.Peer Reviewe

Methods And Sources For Underpinning Airport Ground Movement Decision Support Systems

The airport Ground Movement problem is concerned with the allo- cation of routes to aircraft for their travel along taxiways between the runway and the stands. It is important to find high quality solutions to this problem because it has a strong influence on the capacity of an airport and upon the environmental impact. The problem is particularly challenging. It has multiple objectives (such as minimising taxi time and fuel consumption). It also has considerable uncertainty, which arises from the complex operations of an airport. It is an active and topical area of research. A barrier to scientific research in this area is the lack of publicly available realistic data and benchmark problems. The reason for this is often concerned with commercial sensitivities. We have worked with airports and service providers to address this issue, by exploring several sources of freely-available data and developing algorithms for cleaning and processing the data into a more suitable form. The result is a system to generate datasets that are realistic, and that facilitate research with the potential to improve on real-world problems, without the confidentiality and commercial licensing issues usually associated with real airport data. Case studies with several international airports demonstrate the usefulness of the datasets. The algorithms have been implemented within three tools and made freely-available for researchers. A benchmark Ground Movement problem has also been made available, with results for an existing Ground Movement algorithm. It is intended that these contributions will underpin the advance of research in this difficult application area

Probabilistic Airline Reserve Crew Scheduling Model

This paper introduces a probabilistic model for airline reserve crew scheduling. The model can be applied to any schedules which consist of a stream of departures from a single airport. We assume that reserve crew demand can be captured by an independent probability of crew absence for each departure. The aim of our model is to assign some fixed number of available reserve crew in such a way that the overall probability of crew unavailability in an uncertain operating environment is minimised. A comparison of different probabilistic objective functions, in terms of the most desirable simulation results, is carried out, complete with an interpretation of the results. A sample of heuristic solution methods are then tested and compared to the optimal solutions on a set of problem instances, based on the best objective function found. The current model can be applied in the early planning phase of reserve crew scheduling, when very little information is known about crew absence related disruptions. The main conclusions include the finding that the probabilistic objective function approach gives solutions whose objective values correlate strongly with the results that these solutions will get on average in repeated simulations. Minimisation of the sum of the probabilities of crew unavailability was observed to be the best surrogate objective function for reserve crew schedules that perform well in simulation. A list of extensions that could be made to the model is then provided, followed by conclusions that summarise the findings and important results obtained

Optimal Design and Synthesis of MEA Power System Architectures considering Reliability Specifications

IEEE Aircraft electrification requires novel designs to supply the growing demand for electric power on-board through efficient and reliable production and distribution of electrical energy. Moreover, the aircraft power system will be a key enabler for the integration of future technologies. Pledging to these intentions, we propose a formulation to synthesize a power system architecture that complies with safety specifications following a Platform Based Design methodology that optimizes the main aerospace drivers. Due to the non-linear nature of the design problem, this paper presents reliability based MILP network design formulations for topology synthesis. The novelty of this approach relies in the adoption of network design optimization for MEA power system construction that allows explicit design formulations as MILP problems. This approach will provide an effective way to include safety specifications by introducing reliability and resiliency constraints

A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty

Airlines operate in an uncertain environment for many reasons, for example due to the efects of weather, traffic or crew unavailability (due to delay or sickness). This work focuses on airline reserve crew scheduling under crew absence and journey time uncertainty for an airline operating a single hub and spoke network. Reserve crew can be used to cover absent crew or delayed connecting crew. A fixed number of reserve crew are available for scheduling and each requires a daily standby duty start time. Given an airline's crew schedule and aircraft routings we propose a Mixed Integer Programming approach to scheduling the airline's reserve crew. A simulation of the airline's operations with stochastic journey time and crew absence inputs and without reserve crew is used to generate disruption scenarios for the MIPSSM formulation (Mixed Integer Programming Simulation Scenario Model). Each disruption scenario corresponds to a record of all of the disruptions in a simulation for which reserve crew use would have been beneficial. For each disruption in a disruption scenario there is a record of all reserve crew that could have been used to solve or reduce the disruption. This information forms the input to the MIPSSM formulation, which has the objective of finding the reserve schedule that minimises the overall level of disruption over a set of scenarios. Additionally, modifications of the MIPSSM are explored, and a heuristic solution approach and a reserve use policy derived from the MIPSSM are introduced. A heuristic based on the proposed Mixed Integer Programming Simulation Scenario Model or MIPSSM outperforms a range of alternative approaches. The heuristic solution approach suggests that including the right disruption scenarios is as important as ensuring that enough disruption scenarios are added to the MIPSSM