Cooperation of combinatorial solvers for en-route conflict resolution. (May 2020)

• Record Type: Journal Article
• Authors: Wang, Ruixin; Alligier, Richard; Allignol, Cyril; Barnier, Nicolas; Durand, Nicolas; Gondran, Alexandre
• Is Part Of: Transportation research. Volume 114(2020)
• Page Start: 36
• Page End: 58
• Publication Date: 2020-05
• Subjects: Conflict resolution -- Metaheuristics -- Integer linear programming -- Algorithm cooperation; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2020.01.004
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Generic conflict resolution framework to provide benchmark to scientific community. GPU-based conflict detection fast enough to enable real-time applications. 2-phase Memetic Algorithm able to handle feasibility and optimization. Aggregation of ILP model constraints dramatically increases efficiency. Cooperation of exact algorithm and metaheuristic outperforms both on large instances. Abstract: One of the key challenges towards more automation in Air Traffic Control is the resolution of en-route conflicts. In this article we present a generic framework for the conflict resolution problem that clearly separates the trajectory and conflict models from the resolution. It is able to handle any kind of maneuver and detection models, though we propose our own realistic 3D maneuvers and conflict detection that takes into account uncertainties on the positioning of aircraft. Based on these models, realistic scenarios are built, for which potential conflicts are detected using an efficient GPU-based algorithm. The resulting instances of the conflict resolution problem are provided to the community as a public benchmark. To efficiently solve this problem, we also introduce a generic framework for the cooperation of optimization algorithms. The framework benefits from the various optimization algorithms plugged to it by sharing relevant information among them, and is implemented as a distributed application for better performance. We illustrate its behavior on the conflict resolution problem with the cooperation between a Memetic Algorithm and an Integer Linear Program which consistently outperforms previous approaches by orders of magnitude. Instances with up to 60 aircraft are optimally solved within a few minutes using this framework, while each algorithm taken individually only provides sub-optimal solutions. This cooperative approach thus seems appropriate for application in a real-time context.