Enabling Integration and Interaction for Decentralized Artificial Intelligence in Airline Disruption Management

TL;DR

This paper proposes an intelligent multi-agent system using AI and distributed ledger technology to enable rapid, integrated recovery of airline operations during disruptions, addressing multiple problem dimensions simultaneously.

Contribution

It introduces a systematic, agnostic paradigm for integrated airline disruption management leveraging multi-agent systems and blockchain principles, enhancing decision-making capabilities.

Findings

System executes in polynomial time.

Effective in scenarios with complete route network disruptions.

Demonstrates improved coordination across problem dimensions.

Abstract

Airline disruption management traditionally seeks to address three problem dimensions: aircraft scheduling, crew scheduling, and passenger scheduling, in that order. However, current efforts have, at most, only addressed the first two problem dimensions concurrently and do not account for the propagative effects that uncertain scheduling outcomes in one dimension can have on another dimension. In addition, existing approaches for airline disruption management include human specialists who decide on necessary corrective actions for airline schedule disruptions on the day of operation. However, human specialists are limited in their ability to process copious amounts of information imperative for making robust decisions that simultaneously address all problem dimensions during disruption management. Therefore, there is a need to augment the decision-making capabilities of a human specialist with quantitative and qualitative tools that can rationalize complex interactions amongst all dimensions in airline disruption management, and provide objective insights to the specialists in the airline operations control center. To that effect, we provide a discussion and demonstration of an agnostic and systematic paradigm for enabling expeditious simultaneously-integrated recovery of all problem dimensions during airline disruption management, through an intelligent multi-agent system that employs principles from artificial intelligence and distributed ledger technology. Results indicate that our paradigm for simultaneously-integrated recovery executes in polynomial time and is effective when all the flights in the airline route network are disrupted.