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Railway traffic experiences disturbances during operations that cause conflicts between train paths or even deadlock situations. Dispatchers need actions to restore feasibility and limit spreading of delays through the network. To help them in such a task, the dispatching support tool ROMA (Railway traffic Optimization by Means of Alternative graphs) has been implemented in a laboratory environment. This paper reports on enhancements to the underlying train dispatching model as well as to the solution algorithms studied in order to tackle the increased complexity of busy stations with multiple conflicting paths and high service frequencies. Advanced train reordering and rerouting techniques are compared with straightforward rules and the current approach in the Netherlands. Extensive computational studies based on accepted statistical distributions of train delays for Utrecht Central Station assess the effectiveness of the ROMA tool in terms of solution quality and computation time.

This study addresses the real-time problem of aircraft conflict detection and resolution in a terminal manoeuvring area (TMA). The problem is to take conflict-free airborne decisions on take-off and landing operations at a congested airport. Aircraft control actions at air segments and runways include timing, sequencing, holding and routing. Rescheduling and rerouting decisions aim at balancing the runway workload while minimising delay propagation. This problem can be viewed as a job shop scheduling problem with additional real-world constraints. Two formulations are analysed in which air segments, runways and holdings are modelled explicitly. In the first formulation the entrance time of each aircraft in the TMA is fixed, in the second it can be defined by the procedure. A truncated branch and bound algorithm computes aircraft schedules with fixed routes. The branch and bound is then incorporated in a tabu search scheme for aircraft rerouting. The solution approach is tested on the Rome Fiumicino airport, the main Italian airport, under congested traffic conditions and for several aircraft delay configurations. Computational results show a significant delay reduction when real-time rerouting is allowed in combination with rescheduling with respect to real-time rescheduling with fixed routes. The improvement is larger for the second formulation. © 2012 The Institution of Engineering and Technology.

This paper describes how, in the Netherlands, the railway network is heavily used by heterogeneous train traffic and characterized by short headway times. That is why even small initial delays may perturb the timetable causing consecutive delays. In such conflict situations, traffic controllers have the complicated task to decide upon the optimal train schedule in real-time. They could be assisted by sophisticated conflict-solving systems. Optimal train running profiles can be designed which fit better to the new train order and allow reducing delays and energy consumption at the same time. The paper presents a formulation for this complex problem that makes it suitable for quantitative analysis and for optimizing actual running times at network scale. A conflict solution system is developed, that models the train scheduling problem as an alternative graph. Adopting the blocking time model, safe headway distances between trains are assured by any real-time traffic control measure. The optimal solution from a network point of view can be improved by modifying the speed profiles locally for the individual train routes. A constructive heuristic algorithm for the dynamic modification of running times during operations is proposed that satisfies the timetable constraints of train orders and routes and guarantees the feasibility of the running profile, while taking into account the properties of the signaling and train protection systems in use. A real-world example from the Netherlands in case of the Dutch signaling system NS54 is presented to demonstrate the benefits of the proposed methodology.

This chapter is the first thorough assessment of a full implementation of the concept of dynamic traffic management in combination with advanced optimization tools. In the last years, several studies on partial implementations of this concept have been carried out reporting promising results. The development of new strategies for railway traffic control experienced an increasing interest due to the expected growth of traffic demand and to the limited possibilities of enhancing the infrastructure, which increase the needs for efficient use of resources and the pressure on traffic controllers. Improving the efficiency requires advanced decision support tools that accurately monitor the current train positions and dynamics, and other operating conditions, predict the potential conflicts and reschedule trains in real-time such that consecutive delays are minimized. We carry on our study using an innovative computerized railway traffic management system, called ROMA (Railway traffic Optimization by Means of Alternative graphs). An extensive computational study is carried out, based on two complex and busy dispatching areas of the Dutch rail network. We study practical size instances and different types of disturbances, including train delays and blocked tracks. Our results show the high potential of ROMA as a support tool to improve punctuality through intelligent use of the rail infrastructure and efficient use of the available transport capacity.

This paper addresses the problem of train conflict detection and resolution, which is dealt every day by traffic controllers to adapt the timetable to delays and other unpredictable events occurring in real-time. We describe a number of algorithmic improvements implemented in the real-time traffic management system ROMA (Railway traffic Optimization by Means of Alternative graphs), achieved by incorporating effective rescheduling algorithms and local rerouting strategies in a tabu search scheme. We alternate a fast heuristic and a truncated branch and bound algorithm for computing train schedules within a short computation time, and investigate the effectiveness of using different neighborhood structures for train rerouting. The computational experiments are based on practical size instances from a dispatching area of the Dutch railway network and include complex disturbances with multiple late trains and blocked tracks. Several small instances are solved to optimality in order to compare the heuristic solutions with the optimum. For small instances, the new tabu search algorithms find optimal solutions. For large instances, the solutions generated by the new algorithms after 20 s of computation are up to more than 15% better than those achieved within 180 s by the previous version of ROMA.

This paper studies the problem of sequencing aircraft take-off and landing operations at congested airports. We introduce and analyze alternative detailed formulations and solution algorithms for scheduling arrival and departure times of the aircrafts, such that the delay with respect to the scheduled times is minimized. The aircraft scheduling problem (ASP) is viewed as an extension of the job shop scheduling problem with additional real-world constraints and formulated by using alternative graphs. Two alternative formulations model the required time separation among aircrafts in air segments and runways according to safety regulations and differ for the level of detail used to represent the holding circles. Scheduling rules, heuristic and exact methods are implemented and tested on practical size instances of the Fiumicino airport, the busiest airport in Italy. We show that two versions of an innovative branch and bound algorithm are always able to find good solutions in a few seconds and often improve the best solution computed by the scheduling heuristics. Optimality is proved in less than two minutes for more than half of the instances.

Traffic controllers monitor railway traffic sequencing train movements and setting routes with the aim of ensuring smooth train behaviour and limiting as much as existing delays. Due to the strict time limit available for computing a new timetable during operations, which so far is rather infeasible by using existing tools, railway traffic controllers usually restrict themselves mostly to a few manual timetable modifications and the chosen traffic control actions may be often sub-optimal. This PhD thesis is principally concerned with the design, implementation and evaluation of an advanced and robust laboratory tool for supporting railway traffic controllers in the everyday task of managing timetable disturbances. This dynamic traffic control system co-ordinates the speed of successive trains on open track, solves expected route conflicts and provides dynamic use of platform tracks in stations or alternative paths in a corridor between stations. Blocking time theory for modeling track occupation and signaling constraints is combined with alternative graphs for solving dynamic traffic control problems with the aim of increasing the punctuality and the use of infrastructure capacity at a network scale. The feasibility of the dispatching options is verified in a very short computation time by dynamic updating of the corresponding headways, train speeds and blocking time graphs, while the costs of the alternative dispatching options are measured in terms of maximum and average delays between consecutive trains at stations and other relevant points within the investigated network. To this end, the following achievements are included: (i) An innovative model for railway traffic optimization is presented to predict accurately train traffic flows and to enable the computation of optimal network schedules, i.e., all trains are managed simultaneously in a railway network for a given time period. (ii) The development of fast and effective scheduling algorithms based on the proposed model for the real-time management of a complex railway network is addressed. The objectives are to predict the evolution of train traffic within short computation times and to improve the punctuality by pro-actively detecting and solving train conflicts. (iii) A better use of rail capacity and a further improvement of punctuality are achieved by an iterative adjustment of train orders and routes in case of disturbances. Novel problem dedicated algorithms highlight the potential use of rerouting instead of only rescheduling the trains in order to limit the delay propagation as much as possible. (iv) Constructive algorithms for the dynamic modification of running times are provided that satisfy the timetable constraints of train orders and routes and guarantee the real-time feasibility of the running times, while respecting the signaling and safety systems in use. (v) A temporal decomposition method is introduced for the short-term traffic planning and control over a time period of up to several hours. This approach is of interest for traffic controllers since delays between running trains propagate considerably in time and space during heavily perturbed operations. (vi) A large set of computational studies on real-world instances proves that the automated decision support tool provides better solutions in terms of delay minimization compared to dispatching rules adopted by traffic controllers. Test beds are the hourly timetables of the Schiphol railway bottleneck and of the Utrecht - Den Bosch dispatching area. We study practical size instances and different types of disturbances, including multiple delayed trains, dwell time perturbations and blockage of some tracks.

Railway rescheduling is the task of restoring feasibility in case of disturbances and limiting the propagation of delays through a railway network. This task becomes more difficult when dealing with complex interlocking areas, since operational rules constrain the passage of trains through short track sections. This paper presents a detailed microscopic representation of the railway network that is able to tackle the complexity of a station area with multiple conflicting routes and high service frequency. Two alternative graph formulations are presented to model the incompatibility between routes: one based on track sections and another based on the aggregation of track sections into station routes. An extensive computational study gives useful information on the performance of the two formulations for different disturbance scenarios.

Rescheduling train traffic in a busy and complex railway area is a challenging task, partly because of the high number of constraints to be taken into account, and partly because of the many variables involved. Currently this task is performed almost exclusively by human traffic operators. Previous attempts to provide an automated decision support system have been limited to identifying and solving train conflicts locally. Recently innovative dispatching support tools have been presented that are able to cope with large (real-time) timetable perturbations, such as train delays and their propagation. However, there is a lack of computational studies that underline their additional practical value. In this paper we compare two advanced support systems for real-time rescheduling of train operations, developed for the German and Dutch railway networks. The research aim is to establish a bench mark for future co-operation and exchange of innovative solutions. A common test case from the Dutch railway network, the dispatching area between Utrecht and Den Bosch, and disturbed traffic conditions are studied to evaluate the two dispatching support tools in terms of delay minimization. Since these tools make use of differentmathematical optimization techniques for the computation of running times and train sequences, a detailed comparison of the proposed rescheduling solutions is provided. The use of railway capacity is illustrated in order to enable an easy and fast detection of the conflicts between the trains running in the network and to get precise information about their resolution by the different rescheduling techniques. Keywords: decision support, computer techniques, dynamic train regulations., WIT Transactions on the Built Environment, 103, ISSN:1743-3509, ISSN:1744-7151, ISSN:1746-4498, Computers in Railways XI

In the last years, real-time railway traffic optimization experienced an increasing interest due to the expected growth of traffic and the limited possibilities of enhancing the infrastructure, which ask for a more efficient use of resources and the application of more advanced decision support tools. This paper presents a computerized train dispatching system, called ROMA (Railway traffic Optimization by Means of Alternative graphs), for supporting railway traffic controllers during operations. Innovative scheduling and rerouting algorithms have been developed in order to globally optimize disturbed railway traffic conditions. ROMA can anticipate the evolution of traffic, including the propagation of delays in a regional railway network, and can estimate the effects of different dispatching measures during a period of about 15 minutes ahead. Therefore, ROMA would enable traffic controllers to frequently perform incremental changes to the actual timetable to accommodate changes in traffic patterns due to disturbances, such as train delays and blocked tracks. An extensive computational study is carried out, based on a dispatching area of the Dutch railway network, to show the high potential of our train dispatching system as a support tool to improve punctuality.

A standard practice to improve punctuality of railway services is the addition of time reserves in the timetable to recover perturbations occurring in operations. However, time reserves reduce line capacity, and the amount of time reserves that can be inserted in congested areas is, therefore, limited. In this paper, we investigate the new concept of flexible timetable as an effective policy to improve punctuality without decreasing the capacity usage of the lines. The principle of a flexible timetable is to plan less in the timetable and to solve more inter-train conflicts during operations. The larger degree of freedom left to real-time management offers better chance to recover disturbances. We illustrate a detailed model for conflict resolution, based on the alternative graph formulation, and analyze different algorithms for resolving conflicts, based on simple local rules or global optimization. We compare the solutions obtained for different levels of flexibility and buffer time inserted in the timetable. An extensive computational study, based on a bottleneck area of the Dutch railway network, confirms that flexibility is a promising concept to improve train punctuality and to increase the throughput of a railway network.

Traffic controllers regulate railway traffic by sequencing train movements and setting routes with the aim of ensuring smooth train behaviour and limiting, as much as possible, train delays. In this paper, we describe the implementation of a real-time traffic management system, called ROMA (Railway traffic Optimization by Means of Alternative graphs), to support controllers in the everyday task of managing disturbances. We make use of a branch-and-bound algorithm for sequencing train movements, while a local search algorithm is developed for rerouting optimization purposes. The compound problem of routing and sequencing trains is approached iteratively, computing an optimal train sequencing for given train routes and then improving this solution by locally rerouting some trains. An extensive computational study is carried out, based on a dispatching area of the Dutch railway network. We study practical size instances, and include in the model important operational constraints, including rolling stock and passenger connections. Different types of disturbances are analysed, including train delays and blocked tracks. Comparison with common dispatching practice shows the high potential of the system as an effective support tool to improve punctuality.

In order to face the expected growth of transport demand in the next years, several new traffic control policies have been proposed and analyzed both to generate timetables and to effectively manage the traffic in real-time. In this paper, a detailed optimization model is used to analyze one such policy, called green wave, which consists in letting trains wait at the stations to avoid speed profile modifications in open corridors. Such policy is expected to be especially effective when the corridors are the bottleneck of the network. However, there is a lack of quantitative studies on the real-time effects of using this policy. To this end, this work shows a comparison of the delays obtained when trains are allowed or not to change their speed profile in open corridors. An extensive computational study is described for two practical dispatching areas of the Dutch railway network.

The paper studies a train scheduling problem faced by railway infrastructure managers during real-time traffic control. When train operations are perturbed, a new conflict-free timetable of feasible arrival and departure times needs to be re-computed, such that the deviation from the original one is minimized. The problem can be viewed as a huge job shop scheduling problem with no-store constraints. We make use of a careful estimation of time separation among trains, and model the scheduling problem with an alternative graph formulation. We develop a branch and bound algorithm which includes implication rules enabling to speed up the computation. An experimental study, based on a bottleneck area of the Dutch rail network, shows that a truncated version of the algorithm provides proven optimal or near optimal solutions within short time limits.

The aim of this study was to assess the microbial characteristics of a batch of Conciato Romano during manufacturing and ripening. Conciato Romano is a traditional cheese made from raw sheep’s milk without starter cultures in the province of Caserta (Southern Italy) using traditional methods. A total of 7 samples (raw milk, curd and cheese wheels taken after 25, 60, 120 and 180 days of ripening) were screened for hygiene indicators microorganisms counts (total viable count, Enterobacteriaceae, total coliforms, E. coli, clostridia sulphite reducing, yeasts, coagulasepositive staphylococci, enterococci), for autochthonous lactic acid flora counts (mesophilic and thermophilic lactococci and lattobacilli), and also for Salmonella spp. and Listeria monocytogenes presence. In raw milk, low values were detected for total aerobic flora (3.2 log cfu/mL), Enterobacteriaceae and total coliforms (2 cfu/mL), and the autochthonous starter lactic flora was predominant (3.2 log cfu/mL). During ripening, total aerobic flora was constant (107-108 cfu/g); total coliforms, E. coli, Enterobacteriaceae and yeasts were not detected starting from the 60th day of ripening. Enterococci ranged from 4.2 to 6.2 log cfu/g. The mesophilic lactic flora was dominant with values always >6 log cfu/g during the whole ripening period. Pathogens were never detected. The results of this study highlighted how the raw milk indigenous lactic flora, the traditional production techniques and the cheesemaker’s experience are essential to guarantee the unique nature of Conciato Romano.

This paper addresses the real-time problem of aircraft scheduling and routing in terminal control area. A main task of traffic controllers is to mitigate the effects of severe traffic disturbances on the day of operations in the Terminal Control Area (TCA) of an airport. When managing disturbed take-off and landing operations, they need to minimize the delay propagation and, in addition, to reduce the aircraft travel time and energy consumption. The paper tackles the problem of developing effective decision support tools for air traffic monitoring and control in a busy TCA. To this purpose, centralized and rolling horizon traffic control paradigms are implemented and compared. The mathematical formulation is a detailed model of air traffic flows in the TCA based on alternative graphs, that are generalized disjunctive graphs. As for the aircraft scheduling and (re-)routing approaches, the First-In-First-Out (FIFO) rule, used as a surrogate for the behavior of air traffic controllers, is compared with various optimization-based approaches including a branch and bound algorithm for aircraft scheduling with fixed routes, a combined branch and bound and tabu search algorithm for aircraft scheduling and re-routing, and a mixed integer linear programming formulation for simultaneous scheduling and routing. Various hypothetical disturbance scenarios are simulated for a real-world airport case study, Milano Malpensa, and the proposed timing and routing approaches are compared in terms of their performance in the different scenarios. The disturbed traffic situations are generated by simulating multiple delayed arriving/departing aircraft and a temporarily disrupted runway. In general, the optimization approaches are found to improve the solutions significantly compared to FIFO, in terms of aircraft delay minimization. However, there are some trade-offs involved in picking the right approach and paradigms for practical implementations.

The paper applies principles of dynamic traffic management to solve the train re-scheduling problem faced by railway infrastructure managers during operations. When train operations are perturbed conflicts arise with respect to the scheduled train paths. A detailed mathematical formulation and dispatching algorithms are adopted to re-compute a new timetable of feasible arrival and departure times. The system generates a conflict free schedule with admissible train dynamics and with observance of minimum safety headway distances. Computational experiments on a part of the Dutch rail network show that the adopted rescheduling support system provides better solutions when compared to simple dispatching rules.

This research aimed to evaluate the effects of the inclusion of honey bee pollen (HBP) in meagre (Argyrosoumus regius) juveniles&rsquo, diets on growth performance, diet digestibility, intestinal morphology, and immunohistochemistry. Furthermore, stress-related molecular markers and biochemical blood profile of fish were evaluated, together with mineral trace and toxic element concentration in pollen and diets. Specimens of meagre (360) of 3.34 &plusmn, 0.14 g initial body weight, were randomly allocated to twelve 500 L circular tanks (30 fish per tank). Four diets were formulated: a control diet and three experimental diets with 1%, 2.5%, and 4% of HBP inclusion. All the growth parameters and crude protein and ether extract digestibility coefficients were negatively linearly affected by increased HBP inclusion (p &lt, 0.0001). Histology of medium intestine showed slight signs of alterations in group HPB1 and HPB2.5 compared to control. Fish from HBP4 group showed severe alterations at the intestinal mucosa level. Immunohistochemical detection of TNF-&alpha, in the medium intestine showed the presence of TNF-&alpha, + cells in the lamina propria, which resulted in accordance with the increased level of the TNF-&alpha, protein detected by immunoblotting in the liver. This stress situation was confirmed by the increased hepatic level of HSP70 (p &lt, 0.05) in fish fed the HBP4 diet and by the linear decrease of total serum protein levels in HBP-containing diets (p &lt, 0.0001). These negative effects can be related to the ultrastructure of the bee pollen grain walls, which make the bioactive substances unavailable and can irritate the intestine of a carnivorous fish such as meagre.