Agent-based simulation framework for airport collaborative decision making

Airport Collaborative Decision Making is based on information sharing. A better use of resources can be attained when the different stakeholders at airport operations share their more accurate and updated information. One of the main difficulties when dealing with this information sharing concept is the number of stakeholders involved and their different interest and behaviour: aircraft operators, ground handling companies, airport authority, air traffic control and the Central Flow Management Unit. It is paramount to quantify the benefit of an airport collaborative decision making strategy in order to involve all these different organisations. Simulations are required to analyse the overall system and its emerging behaviour. This paper presents the development and initial testing of an agent-based framework, which allows this behavioural analysis to be done. The simulator explicitly represents the different stakeholders involved in the A-CDM and the interactions between them from milestone 1 to 7. This framework allows independent gradual development of local behaviours and optimisation, and a gradual increase on complexity and fidelity on the simulations

Um modelo de planejamento multiagente para a gestão das operações em solo nos aeroportos

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2017.A indústria da aviação consiste em uma série de procedimentos altamente dinâmicos e complexos. Ela exige principalmente dois fatores importantes: tempo e segurança. Um dos principais motivos de atraso de voo é aeronave em solo, pois envolve várias operações com equipes de atendimento ao aeroporto e veículos. A gestão de operações em solo nos aeroportos têm sido apontada como tendo uma forte influência nos atrasos dos voos. As falhas na comunicação e no processo de colaboração entre as partes interessadas são algumas das razões que dificultam a gestão de operações em solo nos aeroportos. Portanto, baseado no método de planejamento multiagente (MAP), que é um método que envolve a coordenação dos recursos e atividades de múltiplos agentes, este trabalho propõe um arcabouço para ajudar na gestão de operações em solo nos aeroportos. O arcabouço proposto possui duas fases. A primeira identifica os serviços e os recursos necessários para o atendimento dos voos em solos; enquanto na segunda fase um plano de execução é criado assim como o monitoramento da sua execução com objetivo de reduzir tanto os atrasos como os custos operacionais. Neste caso, a contribuição deste trabalho inclui um modelo de planejamento multiagente para coordenação das operações em solo nos aeroportos no contexto da estratégia de tomada de decisão colaborativa (A-CDM), o planejamento das atividades de operações em solo e o monitoramento das atividades. Um protótipo foi desenvolvido e as simulações foram elaboradas com base em dados reais para o Aeroporto Internacional de Brasília. Portanto a interface com o sistema foi simulada por meio do tratamento de algumas aeronaves em solo de uma companhia aérea durante um intervalo de tempo definido. Os resultados obtidos foram satisfatórios. O planejamento das operações em solo pode reduzir o custo associado aos atrasos, comprovando a eficácia da modelagem proposta.Aviation industry consists of a series of highly dynamic and complex procedure. It mainly demands two most important factors: time and safety. One of the major reasons of flight delay is aircraft on ground because it involves various operations with airport service teams and vehicles. Airport ground handling operations have been considered as one main influence factor for flight delays due to the unsuccessful information sharing and collaborations among various airport’s stakeholders. Therefore, based on the Multi-Agent Planning (MAP) method which is a method that involves the coordination of the resources and activities of multiple agents, this work proposes a framework to improve airport ground handling management (GHM) operation. The proposed framework comprises two major phases. The first one identifies the services and resources, and the second one creates the plans and coordinates their executions trying to reduce both the delays and the operating costs. In this case, the contribution of this work includes a MAP model to coordinate airport ground handling operation in the context of the airport collaborative decision making (A-CDM) strategy and the planning of the ground handling activities. A prototype was developed and the simulations were performed using actual data from the International Airport of Brasilia. Therefore the interface with the systems was simulated through the evaluation of some aircraft on the ground of an airline company for a defined period of time. The obtained results were satisfactory. The planning of ground handling could reduce the cost associated to the delays, demonstrating the efficacy of the modeling herein proposed

Agent-based simulation framework for airport collaborative decision making

Airport C ollaborative Decision Making (A - CDM) is based on information sharing. A better use of resources can be attained w hen the different stakeholders at airport operations share their more accurate and updated information . One of the main difficulties when dealing with this information sharing concept is the number of stakeholders involved and their different interest and behaviour : aircraft operators , gro und handling companies, airport authority, air traffic control and the Central Flow Management Unit . It is paramount to quantify the benefit of an airport collaborative decision making strategy in order to involve all these different organisations. Simulat ions are required to analyse the overall system and its emerging behaviour . This paper presents the development and initial t est ing of a n agent - based framework , which allows this behavioural analysis to be done . The simulator explicitly represents the diff erent stakeholders involved in the A - CDM and the interactions between them during the 16 milestones defined by EUROCONTROL o n its A - CDM implementation manual . T his framework allows independent gradual development of local behaviours and optimisation, and a gradual increase on complexity and fidelity on the simulationsPeer ReviewedPostprint (published version

“You are not my boss!”: Managing inter-organizational collaboration in German ground handling operations

While inter-organizational coordination among firms in networks has become a widespread phenomenon and the governance of inter-organizational networks has garnered considerable attention in the management literature, the repercussions of the network form for managing and organizing work remain a considerable gap in the literature. Building on Gittell’s concept of relational coordination, we explore the inter-organizational work collaboration in four German airports’ ground handling operations. By zooming-in on ramp agents’ boundary spanning work role, our comparative study illustrates whether and how a collaboration in inter-organizational work processes is brought about in practice. Our findings reveal the various practices ramp agents deploy in order to handle the tensions emerging from divergent organizational jurisdictions and the requirements for collaboration. We also illuminate how the field-level context influences inter-organizational collaboration by setting conditions such as workload and time restrictions in distributed service delivery

Simulation and optimization of a multi-agent system on physical internet enabled interconnected urban logistics.

An urban logistics system is composed of multiple agents, e.g., shippers, carriers, and distribution centers, etc., and multi-modal networks. The structure of Physical Internet (PI) transportation network is different from current logistics practices, and simulation can effectively model a series of PI-approach scenarios. In addition to the baseline model, three more scenarios are enacted based on different characteristics: shared trucks, shared hubs, and shared flows with other less-than-truckload shipments passing through the urban area. Five performance measures, i.e., truck distance per container, mean truck time per container, lead time, CO2 emissions, and transport mean fill rate, are included in the proposed procedures using real data in an urban logistics case. The results show that PI enables a significant improvement of urban transportation efficiency and sustainability. Specifically, truck time per container reduces 26 percent from that of the Private Direct scenario. A 42 percent reduction of CO2 emissions is made from the current logistics practice. The fill rate of truckload is increased by almost 33 percent, whereas the relevant longer distance per container and the lead time has been increased by an acceptable range. Next, the dissertation applies an auction mechanism in the PI network. Within the auction-based transportation planning approach, a model is developed to match the requests and the transport services in transport marketplaces and maximize the carriers’ revenue. In such transportation planning under the protocol of PI, it is a critical system design problem for decision makers to understand how various parameters through interactions affect this multi-agent system. This study provides a comprehensive three-layer structure model, i.e. agent-based simulation, auction mechanism, and optimization via simulation. In term of simulation, a multi-agent model simulates a complex PI transportation network in the context of sharing economy. Then, an auction mechanism structure is developed to demonstrate a transport selection scheme. With regard of an optimization via simulation approach and sensitivity analysis, it has been provided with insights on effects of combination of decision variables (i.e. truck number and truck capacity) and parameters settings, where results can be drawn by using a case study in an urban freight transportation network. In the end, conclusions and discussions of the studies have been summarized. Additionally, some relevant areas are required for further elaborate research, e.g., operational research on airport gate assignment problems and the simulation modelling of air cargo transportation networks. Due to the complexity of integration with models, I relegate those for future independent research

Inter-organizational Interoperability through integration of Multiagent, Web Service, and Semantic Web Technologies

This paper presents a software architecture for inter-organizational multiagent systems. The architecture integrates Web service technology into multiagent systems to overcome the technical interoperability problem of current multiagent systems in the fast growing service-oriented environments. We integrate Semantic Web technology to make multiagent systems semantically interoperable. We address the problem of interoperability regarding interfaces, messaging protocols, data exchanged, and security whilst considering a dynamic e-business environment. The proposed architecture enables service virtualization, secure service access across organizational boundaries, service-to-agent communication, and OWL reasoning within agents