Simulated Annealing Method-Based Flight Schedule Optimization in Multiairport Systems

Disruptive Innovation in an Institutionalized Environment: Space-based ADS-B in the Air Traffic Management Industry

is a programme to modernise the European Air Traffic Management (ATM) System. It is currently in its feasibility definition study phase which is being co-funded by the European Commission and EUROCONTROL. It is addressing collectively the technological, economic and regulatory aspects associated with ATM. Following the successful completion of definition study phase, it will use the Single European Sky (SES) legislation to synchronise the plans and actions of the different stakeholders in ATM and federate the resources needed for the development and implementation of the required improvements throughout Europe; this applying to both the applicable airborne and ground systems domains. The study is being conducted over a 2-year period (which started in March 2006) by the SESAR Consortium, a grouping which, for the first time in ATM history, has brought together the major stakeholders in European aviation to develop a common vision of the future ATM System. The SESAR Consortium draws upon the expertise of the major organisations within the aviation industry. This includes airspace users, air navigation service providers (ANSPs), airport operators and the supply industry (European and non-European), plus a number of associated partners, including safety regulators, military organisations, staff associations (including pilots, controllers and engineers) and research centres which work together with significant expertise being provided by EUROCONTROL. The study will produce an agreed Master Plan of the research, development and implementation plans and actions needed to be taken by the different stakeholders to realise the future European ATM System. This Plan is developed through the production of 6 main deliverables over the 2 years and covers all aspects of the future System, including its supporting institutional framework. The scope of each the 6 deliverables (D1 to D6) is as follows : D1: Air Transport Framework – the Current Situation D2: Air Transport Framework – the Performance Target D3: Definition of the future ATM Target Concept D4: Selection of the “Best” Deployment Scenario D5: Production of the ATM Master Plan D6: Work Programme for 2008–2013. This paper will summarise the progress made to date by describing the results achieved within the deliverables D1 to D3. In outline terms, these cover : a summary snapshot of the current situation to identify the main areas of improvement; an assessment of the future air transport market place into which future ATM services will be delivered; the management and performance frameworks which will govern the future operation of the System and its further evolution; an initial set of performance requirements which the future System must meet; the nature of the Future ATM Target Concept, this comprising the concept of operations to be adopted; structure of the overall architecture needed for the System; set of technologies to be developed and used to implement it.

The escalation in air traffic demand has precipitated the establishment of the multi-airport systems aimed at effectively handling the influx of flights. Nevertheless, these multi-airport systems encounter airspace resource conflicts during the departure phase, rendering resolution challenging when airports operate on separate schedules. Collaborative departure scheduling has been identified as a promising and effective solution to address these challenges. However, the collaborative departure scheduling presents inherent complexity as an NP-hard problem. In sight of this, this paper proposes a two-step optimization framework to address this typical NP-hard optimization problem. In the first step, the take-off time of each flight is optimized in the first step, so as to minimize flight delays and scheduling chaos. Subsequently, the framework proceeds to optimize the standard instrument departure (SID) based on the optimal take-off time. A multi-agent reinforcement learning (MARL) approach is implemented in both of the two steps to optimize take-off times and select SIDs, respectively. The trained model can quickly collaborate departure scheduling in various situations, reducing flight delays, scheduling chaos, and departure distances compared to solutions generated by First Come First Served (FCFS) principle. The proposed framework and approach are tested on real air traffic data from the Beijing-Tianjin-Hebei region in Northern China. The results show that the MARL-based collaborative departure scheduling has promising applications in multi-airport systems and offers a scalable, adaptive, and efficient solution to this complex problem.

Aiming at the phenomenon of a large number of flight delays in the terminal area makes a reasonable scheduling for the approach and departure flights, which will minimize flight delay losses and improve runway utilization. This paper considered factors such as operating conditions and safety interval of multi runways; the maximum throughput and minimum flight delay losses as well as robustness were taken as objective functions; the model of optimization scheduling of approach and departure flights was established. Finally, the genetic algorithm was introduced to solve the model. The results showed that, in the program whose advance is not counted as a loss, its runway throughput is improved by 18.4%, the delay losses are reduced by 85.8%, and the robustness is increased by 20% compared with the results of FCFS (first come first served) algorithm, while, compared with the program whose advance is counted as a loss, the runway throughput is improved by 15.16%, flight delay losses are decreased by 75.64%, and the robustness is also increased by 20%. The algorithm can improve the efficiency and reduce delay losses effectively and reduce the workload of controllers, thereby improving economic results.

‘Indra’, the Spanish IT leading company, committed to the EU programmes and SESAR in particular, is playing a leading role among the ground industry manufacturers in the domain of Air Traffic Management (ATM) and Airport technologies. Three elements have to be reinforced: cooperation between ANSPs (Air Navigation Service Providers) and ground technology suppliers, collaboration between ANSPs in major developments, partnership between the public sector and the industry.

A combined strategy of an improved simulated annealing (SA) algorithm and genetic algorithm is presented, with the goal of reducing the computational expenses. The improvements made on the SA algorithm include two parts, i.e., the adaptive regulating for the step vector, and the dynamic testing for the equilibrium of the Metropolis process. The proposed strategy has both the advantage of SA algorithm, the ability to avoid being trapped in a local optimum, and that of genetic algorithm, the ability to use the information about the searched states for the next iteration. A practical application on geometry optimization of pole shoes in large salient pole synchronous generators is effectively implemented using the strategy. The numerical results show that the number of iterations used by executing the combined strategy are only about 75% of those by executing basic SA algorithm.

Since 2010, air navigation service providers have been mandated to implement a positive and proactive safety culture based on shared beliefs, assumptions, and values regarding safety. This mandate raised the need to develop and validate a concept and tools to assess the level of safety culture in organizations. An initial set of 40 safety culture questions based on eight themes underwent psychometric validation. Principal component analysis was applied to data from 282 air traffic management staff, producing a five-factor model of informed culture, reporting and learning culture, just culture, and flexible culture, as well as management’s safety attitudes. This five-factor solution was validated across two different occupational groups and assessment dates (construct validity). Criterion validity was partly achieved by predicting safety-relevant behavior on the job through three out of five safety culture scores. Results indicated a nonlinear relationship with safety culture scales. Overall the proposed concept proved reliable and valid with respect to safety culture development, providing a robust foundation for managers, safety experts, and operational and safety researchers to measure and further improve the level of safety culture within the air traffic management context.

With the rapid increase in local and global air traffic, the system-wide operational information exchange and life-cycle management technologies are required to improve the capacity, safety and efficiency of Air Traffic Management (ATM) system. The System Wide Information Management (SWIM) concept is to change the conventional ATM information architecture from point-to-point data exchanges to system-wide interoperability. In this paper, the concept, architecture and design technologies of a real-time oriented multi-layer SWIM system architecture for service assurance are discussed. Moreover, to promote the development of SWIM, the project of Mini Global demonstration has been conducted by the Federal Aviation Administration (FAA) to exchange air transportation information among different Air Navigation Service Providers (ANSPs) by using standardized information exchange models. This paper also introduces the results of this demonstration and the lessons learned from this experience.

For current socio-technical systems, the need for enhanced methods and models for safety management emerges owing to their increasing inherent complexity. The Air Traffic Management (ATM) system represents one of these systems, for which a new perspective is mandatory in terms of safety management. The traditional perspective on safety (Safety-I) has to be reinforced with a new one (Safety-II), integrating the principles of Resilience Engineering. This latter, recurrent in several domains, is receiving an increasing interest in the area of safety and risk management over the past decade. This paper aims to develop a new method, i.e. the RAG-SAT (Resilience Analysis Grid - State Assessment Tool), to combine the principles of Safety-I and Safety-II. It combines a semi-quantitative analysis of system functioning, linking directly resilience with system state and then system risk exposure. The RAG-SAT integrates the technical, human, procedural and environmental aspects of the ATM system, following the Air Navigation Service Provider's (ANSP) perspective. The method is discussed following an explorative conceptual perspective.

EU Emissions Trading scheme in aviation: Policy analysis and suggestions

Summary The Simulated Annealing (SA) algorithm has been widely used in geophysical data processing. However, the seri al SA algorithm is limited by low computing efficiency. In this paper, the annealing schedule has been improved in the SA algorithm, and a constrained inversion of magnetotelluric (MT) data using the parallel SA algorithm has been applied. The test of synthetic data shows that the improved Very Fast Simulated Annealing (VFSA) method is significantly better than the traditional method. Additionally, the computing efficiency has been improved using the parallel SA inversion algorithm. This method has also been applied in MT data processing for geothermal exploration and good geological results have been achieved.

Over time, the rapid expansion of civil aviation infrastructure has led to the establishment of multi-airport systems (MASs) or Metroplex, where airports situated in close proximity form interconnected networks. Given that individual airport capacities often fall short of meeting flight scheduling demands, devising effective multi-airport flight scheduling methods becomes imperative. This article introduces a novel MAS slot expansion configuration framework centered on coupling terminal areas. In contrast to conventional airport capacity slot expansion approaches, this framework demonstrates superior configurational efficacy within respective airport terminal environments. The model outlined in this research identifies the terminal control sector as the pivotal resource node within the interconnected terminal area, aiming to maximize the total expanded slots while minimizing the overall unfairness among airports within the terminal airspace. Employing the ε-constraint method facilitates the transformation of the minimization objective into solvable constraint conditions. Subsequently, leveraging Beijing Metroplex as a case study, the research devises benchmark, single-airport, multi-airport minimum, and multi-airport maximum scenarios to compare and analyze configuration outcomes in terms of key resource allocation impacts and coupled resource utilization efficiencies. Ultimately, employing the AirTOp fast-time simulation model validates each scenario, demonstrating that the proposed configuration method yields reduced delay levels and fewer conflicts in simulation environments.

The most important mode of long‐distance transportation for people to use time efficiently is air transportation. One of the most significant factors determining air traffic performance is the scheduling created by companies. When creating schedules, various parameters are used, mainly the demand for the determined route, and the availability of airplanes and flight crews. Known climatic conditions on the route are generally neglected. Within the scope of this study, the creation of flight schedules, which are normally the preparation of flight schedules by considering the monthly, daily, and hourly constraints that could cause flight delays, were determined by also considering weather conditions. In this determination process, 32‐year flight data between 1987 and 2018 were used as a basis. Apache Spark, one of the big data technologies, was used to determine these constraints. The scheduling was optimized by using the constraints used to prevent flight delays. It was observed in the results obtained that simulated annealing (SA) achieved the most optimal results compared to the genetic algorithm (GA) and the artificial bee colony (ABC) algorithm. As the dimensions of the searched space increased, solving the problem with metaheuristic approaches was more advantageous in terms of time compared to the classical method.

Synchronised demand-capacity balancing in collaborative air traffic flow management

This paper describes the application of requirements engineering concepts to support the analysis of the impact of new software systems on system-wide goals. Requirements on a new or revised software component of a socio-technical system not only have implications on the goals of the subsystem itself, but they also impact upon the goals of the existing integrated system. In industries such as air traffic management and healthcare, impacts need to be identified and demonstrated in order to assess concerns such as risk, safety, and accuracy. A method called PiLGRIM was developed which integrates means-end relationships within goal modelling with knowledge associated with the application domain. The relationship between domain knowledge and requirements, as described in a satisfaction argument, adds traceability rationale to help determine the impacts of new requirements across a network of heterogeneous actors. We report procedures that human analysts follow to use the concepts of satisfaction arguments in a software tool for i* goal modelling. Results were demonstrated using models and arguments developed in two case studies, each featuring a distinct socio-technical system—a new controlled airspace infringement detection tool for NATS (the UK’s air navigation service provider), and a new version of the UK’s HIV/AIDS patient reporting system. Results provided evidence towards our claims that the conceptual integration of i* and satisfaction arguments is usable and useful to human analysts, and that the PiLGRIM impact analysis procedures and tool support are effective and scalable to model and analyse large and complex socio-technical systems.