Paolo Dell’Olmo

Scheduling Models and Algorithms for TMA Traffic Management

In this paper, models and algorithms for real-time control of the TMA are proposed. We consider two cases: in the first one (static) we assume that there is a set of aircraft to be sequenced for which we know in advance their entry time in the terminal area; in the second one (dynamic), the entry times of future aircraft are unknown and the sequence of aircraft is recomputed whenever a new aircraft approaches the terminal area. For the static case, we model the sequencing problem as a Cumulative Traveling Salesman Problem with Ready Times and propose two lower bounds for testing heuristic solutions. For the dynamic case, where only a limited knowledge of the arrivals is assumed, we add to the basic model a set of constraints which allow the controller to maintain given patterns of the landing sequences previously generated. For both cases, heuristic algorithms are proposed and computational results are discussed.

Scheduling multiprocessor tasks on parallel processors with limited availability

Abstract In this work we consider the problem of scheduling multiprocessor tasks on parallel processors available only in restricted intervals of time called time windows. The multiprocessor task model applies to modern production systems and parallel applications in which several processors can be utilized in parallel. Preemptable tasks are considered. Polynomial time algorithms are given in three cases: the case of maximum lateness criterion and a fixed number of processors, the case of schedule length criterion when tasks have various ready times and require either one or all processors, and in case of schedule length criterion when the sizes of the tasks are powers of 2.

A Model for Real-Time Traffic Coordination Using Simulation Based Optimization

An approximate traffic model, APRES-NET, is proposed for a simulation-based optimization approach for real-time network coordination of traffic flows. The objective of APRES-NET is twofold: to provide network-wide prediction of traffic movements and to evaluate, approximately but quickly, the performance of any signal timing strategy. To make a prediction, it uses the observed network vehicular traffic and signal data for a period of time, a future signal plan, and statistical information on vehicle movement, to predict the traffic for some future time period. The APRES-NET simulation consists of propagating into the future the movement of the vehicles detected in the network during the “last detection period”. To quickly, and approximately, simulate the vehicle movement through the whole network, a simplified queuing mechanism is implemented at the intersections. At an intersection, a turn is assigned to each vehicle based on turning probabilities. Performance measures are calculated continuously as the simulation run is being conducted. APRES-NET is being used for real-time coordination of signal phase timings by making it behave as a “function evaluator” in an iterative optimization scheme. The paper discusses the basic structure and the algorithms used by APRES-NET.

Solving a Preemptive Project Scheduling Problem with Coloring Techniques

In this paper we describe an exact algorithm to solve a preemptive project scheduling problem with scarce resources. As most of the scheduling problems also the studied one is NP-hard. Many different approaches, such as mathematical programming, heuristics, simulating annealing, etc., have been presented to solve this class of intractable problems. In our approach we consider a graph-theoretical method based on new coloring techniques. In particular, given a disjunctive graph we examine the correspondences between an assignment of time windows (i.e. activities starting time and finishing time) and an assignment of colors to the activities of a project, defining when an exact weighted coloring is an optimal preemptive schedule. We present computational results on randomly generated test problems of the branch and bound algorithm proposed. From the results obtained emerges that the possibility to manage hard problems using new coloring techniques seems to be more efficient than others, referring in particular to the performances of the algorithm proposed.

Coordination of Traffic Flows in the TMA

A number of models and algorithms designed to optimize the management of the terminal area have been presented in the literature and/or have been implemented in some airport. Most of them focus their attention mainly on landing operations, while modeling capabilities concentrate on the runway complex, assumed to be a single runway in the simplest case, or, when necessary, examine specific configurations. In this paper, we propose a modeling approach to coordinate inbound and outbound traffic flows on all the prefixed routes, through a discretization of the whole space terminal area. Several operational constraints, like longitudinal and diagonal separations in particular regions of the airspace and different runway configurations (independent, parallel, crossing), can be represented in a uniform framework. In order to assess the model’s capabilities, we describe in detail a case study performed for the Rome Fiumicino airport for which we report also algorithmic results with respect to different performance indices.

Optimal superfluid management of 5G networks

We consider the problem of evaluating the performance of a 5G network based on reusable components, called Reusable Functional Blocks (RFBs), proposed by the Horizon 2020 SUPERFLUIDITY project. RFBs allow a high level of flexibility, agility, portability and high performance. After formally modelling the RFB entities and the network physical nodes, we optimally formulate the problem of maximizing different Key Performance Indicators (KPIs) on an RFB-based network architecture, in which the RFBs are shared among the nodes, and deployed only where and when they are really needed. Our results, obtained by solving the proposed optimization problem over a simple yet representative scenario, show that the network can be managed in a very efficient way. More in depth, the RFBs are placed into the nodes in accordance with the amount of requested traffic from users and the specific pursued KPI, e.g., maximization of user throughput or minimization of the number of used nodes. Moreover, we evaluate the relationship between the capacity of each node and the number of RFBs deployed on it.

Models and Algorithms for Real-Time Control of Aircraft Landings

In this paper, models and algorithms for real-time control of the region around the airport are proposed. We consider the dynamic case in which the entry times of aircraft in the region are unknown and the sequence of aircraft must be recomputed whenever a new aircraft approaches the terminal area. A set of constraints which allow the controller to maintain given patterns of the landing sequences previously generated must be taken into account. Heuristic algorithms are proposed and computational results are discussed.

An Approximation Result for a Bandwidth Allocation Problem

Recent advances in communication technologies have made it possible the integration of heterogeneous traffics of different bandwidths in a single broadband network, achieving the flexibility and the economic advantage of sharing a network. In such a situation, if no traffic access control is exerted, the network resources, such as network bandwidth, will be occupied unfairly resulting in a low throughput usage of the network. Thus, it is needed a traffic control strategy that allocates the network bandwidth fairly to achieve maximum throughput [6]. We consider a radio network where the transmitters request consecutive frequency slots (bandwidth) to transmit their messages of different traffic classes, such as voice, data, video. The problem is to allocating bandwidths to transmitters in order to minimize the overall network bandwidth requirement, and it is called Bandwidth Allocation (BA) problem.

Exact and Heuristic Algorithms for the Jump Number Problem

The jump number problem consists in determining a linear extension, of a partially ordered set (poset), with minimum number of jumps. The problem is known to be NP-hard for generical posets. In the paper we present an exact algorithm based on dynamic programming, and a heuristic algorithm for the jump number problem for general posets. Performance analysis of both algorithms are performed on a number of randomly generated partially ordered sets.

Mathematical Models for On-Line Train Calendars Generation

Abstract In this paper we present a new model for train calendars textual generation, that is a method for automatically generating a text to customers in a concise and clear way with a service calendar represented by a boolean vector as its input. This problem arises in the transportation field, in particular in railway services. A new mathematical model which guarantees the optimality of solutions and good computational performances is described and tested on several real railway timetables, always obtaining optimal solutions. Moreover, it is extensively compared with existing models showing a significant reduction of computational times that makes it applicable in practical contexts.