Seite - 377 - in Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments

A Multi-Agent Negotiation Approach for Airline Operation Control Soufiane Bouarfa Aerospace Engineering, Abu Dhabi Polytechnic, Al Ain, United Arab Emirates Reyhan Aydoğan Department of Computer Science, Özyeğin University, İstanbul, Turkey Alexei Sharpanskykh Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands Abstract - This paper proposes and evaluates a new airline disruption management policy using agent-based modelling, simulation, and verification. The new policy is based on a multi-agent negotiation protocol and is compared with three airline policies based on established industry practices. The application concerns Airline Operations Control whose core functionality is disruption management. In order to evaluate the new policy, a rule-based agent-based model of the AOC and crew processes has been developed. This model is used to assess the effects of multi-agent negotiation on airline performance in the context of a challenging disruption scenario. For the specific scenario considered, the multi-agent negotiation policy outperforms the established policies when the agents involved in the negotiation are experts. Another important contribution is that the paper presents a logic-based ontology used for formal modelling and analysis of AOC workflows. Keywords: Workflow modelling, Rule-based modelling, Formal modelling, Multi- agent negotiation, model checking, Airline operations control. 1. Introduction Airlines cope with many disruptions of different nature that implicitly or explicitly test their resilience on a regular basis. These disruptions may interact with each other, potentially creating a cascade of other disturbances that may span over different spatial as well as time scales, ranging from affecting only one aircraft or crew, up to a group of aircraft. In current airline operations, disruptions are managed by Airline Operations Control (AOC), and may impact the economic performance of the airline and customer service. E.g., some flights are rerouted, some aircraft are leased, and some flights are re- booked. Consideration of the aircraft routings, crew, maintenance, weather, customer needs, security and turnaround processes complicate AOC. Current AOC practice consists of a coordination process between many human operators, each of which plays an essential role in disruption management. With the ever-growing complexity and various types of interdependencies between airlines, airports, and ATC centres, maintaining airline resilience to expected and unexpected disruptions becomes a challenging task. In order to manage disruptions in a resilient way, advanced forms of coordination between human operators and automation is required. This paper aims at Intelligent Environments 2019 A. Muñoz et al. (Eds.) © 2019 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/AISE190068 377