## 1 Introduction  
Airport operations are widely recognized to be one of the main bottlenecks of the current Air Traffic Management (ATM) system. The Single European Sky ATM Research (SESAR) program, which is aimed at renovating the European ATM system, is, indeed, also focused on modifying the future airport operations concept, dealt with in the Airport Operations Work Package (WP 6).  
One of the basic principles driving this transformation is the proactive management of airport performance [1], e.g., in terms of capacity. This is done by integration of the local Airport Operations Plan (AOP) in the global Network Operations Plan (NOP) and sharing data across all airport stakeholders, which shall perform timely updates to the AOP under agreed rules and procedures. The reference concept upon which this novel airport operations view is built is Airport-Collaborative Decision-Making (A-CDM), for which a standard term of reference has been recently updated in [2].  
The present paper deals with the problem of managing aircraft movement on an airport surface, taking into account planning and routing functions for aircraft, while being consistent with the airport operations concept envisioned by SESAR [3]. As airport dimensions, complexity and surface traffic steadily increase, the current first-come first-served approach with conflict detection and resolution performed by Air Traffic Controllers (ATCo) is not capable of dealing efficiently with the problem of interest. Automated decision support systems are under study and/or development for supporting ATCos decision-making in selecting the paths of all aircraft and the time to command the off block procedure start for departing ones. The problem is usually tackled describing the airport surface system by network and graph theory. In this way, the ground-movement process is abstracted into a mixed-integer-continuous-program [4; 5; 6; 7; 8; 9], which is either linearized, yielding a Mixed-Integer-Linear-Problem (MILP) [4; 5; 6; 7], or approached by stochastic optimization algorithms [8]. A thorough overview of possible problem settings and popular approaches can be found in [9], to which the interested reader can refer. The common trait of the usual ground movement problem's formulations is that they easily result in a computationally intractable problem, and some simplifying assumptions must be introduced, such as bounding aircraft taxi speeds [6], applying a receding horizon approximation [4; 7] and linearizing the continuous problem part [4; 6; 7; 9].  
This paper proposes an algorithm suitable for tackling the ground movement problem. This Taxi Route Planner (XRP) tool aims at minimizing the holding time of aircraft that are maneuvering on airport taxiways, for both arriving and departing aircraft. This is done in two consecutive steps, that is, a standalone, shortest path solution from runway to apron (or _vice versa_), neglecting the presence of other aircraft on the airport surface, followed by a conflict detection and resolution task that attempts to reduce and possibly nullify the number of conflicts generated in the first phase. In this way, the computationally intractable problem is simplified by decomposition, and a suboptimal solution can always be found within a pre-specified time interval, which makes the algorithm suitable for practical use in true-world airport operations.  
The paper is organized as follows. First, a possible scenario for future airport operations, which is taken as a reference in developing the algorithm, is outlined following the latest SESAR's concept of operations. Subsequently, target requirements for the system are derived. Then, the algorithmic structure of the tool is laid out, and its contents discussed in detail. An example application on an Italian airport exemplifies how true-world applications can be modeled to suit the algorithm's needs. Last, a preliminary assessment of the algorithm's performance is presented.