Minimum Cost Design of Cellular Networks in Rural Areas with UAVs, Optical Rings, Solar Panels and Batteries

Bringing the cellular connectivity in rural zones is a big challenge, due to the large installation costs that are incurred when a legacy cellular network based on fixed Base Stations (BSs) is deployed. To tackle this aspect, we consider an alternative architecture composed of UAV-based BSs to provide cellular coverage, ground sites to connect the UAVs with the rest of the network, Solar Panels (SPs) and batteries to recharge the UAVs and to power the ground sites, and a ring of optical fiber links to connect the installed sites. We then target the minimization of the installation costs for the considered UAV-based cellular architecture, by taking into account the constraints of UAVs coverage, SPs energy consumption, levels of the batteries and the deployment of the optical ring. After providing the problem formulation, we derive an innovative methodology to ensure that a single ring of installed optical fibers is deployed. Moreover, we propose a new algorithm, called DIARIZE, to practically tackle the problem. Our results, obtained over a set of representative rural scenarios, show that DIARIZE performs very close to the optimal solution, and in general outperforms a reference design based on fixed BSs

An approximation result for a periodic allocation problem

AbstractIn this paper we study a periodic allocation problem which is a generalization of the dynamic storage allocation problem to the case in which the arrival and departure time of each item is periodically repeated. These problems are equivalent to the interval coloring problem on weighted graphs in which each feasible solution corresponds to an acyclic orientation, and the solution value is equal to the length of the longest weighted path of the oriented graph. Optimal solutions correspond to acyclic orientations having the length of longest weighted path as small as possible. We prove that for the interval coloring problem on a class of circular arc graphs, and hence for a periodic allocation problem, there exists an approximation algorithm that finds a feasible solution whose value is at most two times the optimal

Contributi alla flora vascolare di Toscana. VII (357-439)

New localities and/or confirmations concerning 83 specific and subspecific plant taxa of Tuscan vascular flora, belonging to 71 genera and 33 families are presented: Carpobrotus (Aizoaceae), Alternanthera (Amaranthaceae), Leucojum (Amaryllidaceae), Anacyclus, Andryala, Carduus, Centaurea, Cichorium, Erigeron, Helichrysum, Helminthotheca, Hieracium, Limbarda, Pilosella, Scolymus, Sonchus, Tagetes, Urospermum, Xanthium (Asteraceae), Mahonia (Berberidaceae), Myosotis (Boraginaceae), Biscutella, Ionopsidium, Raphanus, Rapistrum (Brassicaceae), Buxus (Buxaceae), Vaccaria (Caryophyllaceae), Cistus (Cistaceae), Calystegia, Cuscuta (Convolvulaceae), Cymodocea (Cymodoceaceae), Cyperus (Cyperaceae), Amorpha, Emerus, Lathyrus, Lotus, Ononis, Trifolium, Vicia (Fabaceae), Quercus (Fagaceae), Geranium (Geraniaceae), Myriophyllum (Haloragaceae), Malva (Malvaceae), Epipogium, Himantoglossum (Orchidaceae), Orobanche (Orobanchaceae), Osyris (Santalaceae), Oxalis (Oxalidaceae), Pinus (Pinaceae), Anisantha, Avellinia, Avena, Corynephorus, Crypsis, Cutandia, Elytrigia, Lolium, Panicum, Polypogon, Sporobolus (Poaceae), Rumex (Polygonaceae), Lysimachia (Primulaceae), Eranthis, Ranunculus (Ranunculaceae), Rubus (Rosaceae), Crucianella, Galium (Rubiaceae), Verbascum (Scrophulariaceae), Solanum (Solanaceae), Tamarix (Tamaricaceae), Viola (Violaceae). In the end, the conservation status of the units and eventual protection of the cited biotopes are discussed

A dynamic programming approach for the airport capacity allocation problem

In most of the optimization models developed to manage airports operations, arrivals and departures capacities are treated as independent variables: that is the number of flights allowed to take off does not affect the number of landings in any unit of time, and vice versa. This assumption is seldom verified in most of the congested airports, where many interactions between arrivals and departures take place. In this paper, we face the problem of finding the optimal trade‐off between the number of arrivals and departures in order to reduce a delay function of all the flights, using a more realistic representation of the airport capacity, i.e. the capacity envelope. Under the assumption of piecewise linear convex capacity envelopes and of the exact interpolation of all the Pareto‐optimal operational points, we show that the problem can be formulated as a linear programming model. For general airport capacity envelopes, we propose a dynamic programming formulation with a corresponding backward solution algorithm, which is robust, easy to implement and has a linear computational complexity. The algorithm performances are evaluated on different realistic scenarios, and the optimal solutions are compared with those computed by a greedy algorithm, which can be seen as an approximation of the current decision procedures. The percentage deviation of the cost of these two solutions ranges from 3.98 to 35.64

Novel local-search-based approaches to university examination timetabling

Examination timetabling assigns examinations to a given number of time slots so that there are no conflicts. A conflict occurs if a student has to take more than one examination at the same time, or when the number of students that must take an exam exceeds the capacity of the classroom assigned. The objective is to minimize penalties from proximity constraints. We present new algorithms based on local search and report on an extensive experimental study. We consider also a variant where the concern is to produce conflict-free timetables minimizing the number of time slots, regardless of how close exams appear in the schedule. The algorithms proposed also manage the trade-off between the two objective functions and produce the best results on several standard benchmark instances, compared to the best existing algorithms

REALBAND: An Approach for Real-Time Coordination of Traffic Flows on Networks

An approach is proposed for real-time coordination of signal phase timings for a network. Currently, network coordination is done using off-line methods, such as MAXBAND, PASSER II, and TRANSYT, which are based on average traffic volumes for various movements. On-line approaches such as SCOOT adapt off-line methods by constantly inputting updated average volumes computed from detector data over the 'last' decision horizon. REALBAND first identifies platoons and predicts their movement in the network (i.e., their arrival times at intersections, their sizes, and their speeds) by fusing and filtering the traffic data obtained, from various sources, in the last few minutes. An approximate traffic model, APRES-NET, is used to propagate the predicted platoons through the network for a given time horizon. The signals are set so that the predicted platoons are provided appropriate green times to optimize a given performance criterion. If two platoons demanding conflicting movements arrive at an intersection at the same time, then either one or the other will be given priority for green time, or one of them is split to maximize the given measure of performance. This study discusses how such conflicts are resolved and the corresponding algorithmic procedure of REALBAN

Planning activities in a network of logistic platforms with shared resources

This paper has been motivated by the study of a real application, the transshipment container terminal of Gioia Tauro in Italy. The activities in a container terminal concern with the movement of containers from/to mother vessels and feeders and with the handling and storage of containers in the yard. For such type of applications both operational (e.g., scheduling) and tactical (e.g., planning) models, currently available in the literature, are not useful in terms of operations management and resources optimization. Indeed, the former models are too detailed for the complexity of the systems, while the latter are not able to capture the operational constraints in representing those activities which limit the nominal capacity. Herein, the container terminal, or more in general a service or production system, is represented as a network of complex substructures or platforms. The idea is to formalize the concept of platform capacity, which is used to represent the operational aspects of the container terminal in a mathematical model for the tactical planning. The problem, which consists in finding an allocation of resources in each platform in order to minimize the total delay on the overall network and on the time horizon, is modelled by a mathematical programming formulation for which we carry out a computational analysis using CPLEX-MIP solver. Moreover, we present a dynamic programming based heuristic to solve larger instances in short computational time. On all but one of the smaller instances, the heuristic solutions are also optimal. On the larger instances, the maximum gap, i.e. the percentage deviation, between the heuristic solutions and the best solutions computed by CPLEX-MIP within the time limit of 3600 s, has been 6.3%