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Operations control is one of the most important areas for an airline company. Through operations control mechanisms an airline company monitors all the flights checking if they follow the schedule that was previously defined by other areas of the company. Unfortunately, some problems may arise during this stage (Clausen et al., 2005). Those problems can be related with crewmembers, aircrafts and passengers. The Airline Operations Control Centre (AOCC) includes teams of experts specialized in solving the above problems under the supervision of an operation control manager. Each team has a specific goal contributing to the common and general goal of having the airline operation running under as few problems as possible. The process of solving these kinds of problems is known as Disruption Management (Kohl et al., 2004) or Operations Recovery. To select the best solution to a specific problem, it is necessary to include the actual costs in the decision process. One can separate the costs in two categories: Direct Operational Costs (easily quantifiable costs) and Quality Operational Costs (less easily quantifiable costs). Direct operational costs are, for example, crew related costs (salaries, lodgement, extra-crew travel, etc.) and aircraft/flights cost (fuel, approach and route taxes, handling services, line maintenance, etc.). The quality operational costs that AOCC is interested in calculating are, usually, related with passengers satisfaction. Specifically, we want to include in the decision process the estimated cost of delaying or cancelling a flight from the passenger point of view, that is, in terms of the importance that such a delay will have to the passenger. In this chapter we present our intelligent agent-based approach to help the AOCC solving the disruption management problem. It is organized as follows: In Section 2 we present some related regarding operations recovery, a classification of current tools and systems in use in some airline companies and a brief summary of the current use of software agents’ technology in other domains. Section 3 introduces the Airline Operations Control Centre (AOCC), including typical organizations and problems, the current disruption management (DM) process and a description of the main costs involved. Section 4 is the main section of this chapter and presents our agent-based approach to this problem. This section presents: (i) the reasons that made us adopt the software agents and multi-agent system (MAS) paradigm; (ii) the MAS architecture including the specific agents, roles and protocols as well as some relevant agent characteristics like autonomy and social-awareness; (iii) decision 6

Disruption Management in Airline Operations Control – An Intelligent Agent-Based Approach