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Abstract The optimization of the train frequency of the Airport express line (AEL) is crucial for improving the efficiency of air-rail intermodal transport. It directly influences passenger transfer convenience and overall service quality, thereby bolstering the competitiveness of the transport system This study focuses on the optimization of “AEL and Flight Succession” in the context of air-rail intermodal transport. By analyzing the departure and landing time of airport flights, we assess the demand from various passenger flows and identify key factors that impact the connection between the AEL and flights. Based on these factors, we develop a demand-driven optimization model for AEL frequency, aimed at minimizing total travel time and the number of unserved passengers. A simulated annealing algorithm is employed to solve this model. The Lanzhou-Zhongchuan AEL serves as a case study for validation. The results demonstrate that the optimized schedule reduces total passenger travel time costs by 0.93% and 3.82%, respectively, while accounting for passenger time sensitivity and fairness principles, with a difference of 2.89% between these scenarios. In addition, the optimization scheme decreases the number of unserved passengers by 14.7% and reduces the percentage of flights and trains failing to meet occupancy constraints by 17%. This study illustrates that the schedule optimization strategy not only effectively increases the number of served passengers but also significantly reduces total intermodal and commuter travel time. Such findings provide a solid scientific foundation for AEL operations and management to develop a more efficient and rational train schedule in the context of air-rail intermodal transport.

Line planning and timetabling play important roles in the design of urban rail transportation services. Due to the complexity of the integrated optimization of entire transportation plans, previous studies have generally considered line planning and timetabling design independently, which cannot ensure the global optimality of transportation services. In this study, the integrated design problem of line planning and timetabling was characterized as an equilibrium space–time network design problem and solved with a bi-objective nonlinear integer programming model. The model, in which train overtaking and passenger path choice behavior were considered, adjusted the network topology and link attributes (time and capacity) of the travel space–time network by optimizing the train service frequency, operation zone, stopping pattern, train formation, and train order to minimize the system life cycle cost and total passenger travel time perception. An algorithm was constructed using the non-dominated sorting genetic algorithm II combined with the self-adaptive gradient projection algorithm to solve the model. A real-world case was considered to evaluate the effectiveness of the proposed model and algorithm. The results showed that the model not only performed well in the trade-off between system cost and passenger travel efficiency, but it could also reduce the imbalance of train and station loads. Pareto front analysis of the model with different parameters showed that more types of trains did not correlate with a better performance, some line-planning strategies had a combination effect, and multi-strategy line planning was more suitable for scenarios with a high imbalance in the temporal and spatial distributions of passenger flow. [ABSTRACT FROM AUTHOR]

This paper proposes an optimisation model for an urban rail transit line timetable considering headway coordination between the mainline and the depot during the transition period. The model accounts for the tracking operation scenario of trains inserted from the depot onto the mainline and related train operation constraints. The optimisation objectives are the number of trains inserted, maximum train capacity rate and average headway deviation. Second-generation non-dominated sorting genetic algorithm is designed to solve the model. A case study shows that optimisation achieves a total of 25 trains inserted, a maximum train capacity rate of 0.975 and an average headway deviation of 9.5 s, resulting in significant improvements in train operations and passenger satisfaction. Compared with the current train timetable before optimisation, the average dwell time and the maximum train capacity rate at various stations have been reduced after optimisation. The proposed model and approach can be used for train timetabling optimisation and managing the operations of urban rail transit lines.

The sustainability of rail transport is a highly debated topic. Historically, there has always been strong political support to maintain even lightly used regional lines in operation. However, the economic situation and increasing demands for rail safety have introduced new challenges, including the fundamental question of whether to continue operating a line or discontinue it. So far, no simple solution has been applied across the board. Nevertheless, there are already some Public Service Obligations (PSOs) planning for the next 10 to 15 years, putting pressure on the infrastructure manager to implement measures that guarantee a specific system travel time on the line. If these expectations are not met, they may consider shifting transport services to alternative modes of transport in the medium term. One such region facing this challenge is the Hradec Králové Region, where a thesis was developed to analyze the regional route Doudleby nad Orlicí - Rokytnice v Orlických horách. The study focuses on the technological requirements for achieving the necessary system travel time, which is also the primary goal of this paper.

The paper focuses on the design of an operational concept for the Nymburk–Jičín regional line and its simulation using OpenTrack software, both under the current infrastructure conditions and with anticipated modernization, particularly in the area of security system. It includes an analysis of the current state of the line, the development of several operational concepts, their simulation, and proposed changes necessary for effective implementation. The model setup covers individual elements on the track, stations and interstation sections, including the creation of train routes and timetables. The outcome is a proposal for multiple operational concepts and associated measures for their implementation. The final chapter of the paper deals with proposals for measures that are necessary or suitable for the successful implementation of individual concepts.

In order to ensure punctual and robust service, it is vital to have a good understanding of the current performance of a railway network. Several approaches to doing so exist but lack the ability to compare both service and station performance in a single dimension. The study presented here proposes the use of the Rasch analysis technique within an operational context to compare the relative dwell time performance of stations and services. To do so, we make use of data from commuter trains in Sweden and the UK. The results from the study suggest that the method can be used to study dwell times on a line level and can capture the variability in dwell times. Assessing the model output also shows that the approach adequately reflects the expected variability in both service performance and station difficulty. Comparing the model output to more commonly used indicators for dwell time, we find that the Rasch analysis allows us to better identify cases where planners can make adjustments to reduce the likelihood of dwell time delays. In addition to this, we highlight that a common assumption that more passengers lead to worse dwell times does not hold. Having more in-depth insights into where dwell time performance is troublesome can help planners to make more informed decisions which helps towards improving overall dwell time performance, reducing delays, and improving the attractiveness of trains as a mode of transport.

Line planning and timetabling play important roles in the design of urban rail transportation services. Due to the complexity of the integrated optimization of entire transportation plans, previous studies have generally considered line planning and timetabling design independently, which cannot ensure the global optimality of transportation services. In this study, the integrated design problem of line planning and timetabling was characterized as an equilibrium space–time network design problem and solved with a bi-objective nonlinear integer programming model. The model, in which train overtaking and passenger path choice behavior were considered, adjusted the network topology and link attributes (time and capacity) of the travel space–time network by optimizing the train service frequency, operation zone, stopping pattern, train formation, and train order to minimize the system life cycle cost and total passenger travel time perception. An algorithm was constructed using the non-dominated sorting genetic algorithm II combined with the self-adaptive gradient projection algorithm to solve the model. A real-world case was considered to evaluate the effectiveness of the proposed model and algorithm. The results showed that the model not only performed well in the trade-off between system cost and passenger travel efficiency, but it could also reduce the imbalance of train and station loads. Pareto front analysis of the model with different parameters showed that more types of trains did not correlate with a better performance, some line-planning strategies had a combination effect, and multi-strategy line planning was more suitable for scenarios with a high imbalance in the temporal and spatial distributions of passenger flow.

Due to the COVID-19 pandemic, the demand for public passenger transport has decreased significantly in many European countries since March 2020. Due to several measures and restrictions adopted, this decrease was particularly pronounced in international long-distance transport due to several restrictions and measures adopted. A significant decrease in demand could also be observed on the international rail transport route Bratislava / Vienna – Prague in the form of the decline in the number of transported passengers on this railway line. Therefore, it is very important and necessary to propose various measures to increase the demand and achieve a significant long-term increase in the number of passengers in long-distance rail transport not only on the mentioned transport route. This paper analyses the impacts of the COVID-19 pandemic on passenger transport usage frequency and proposes solutions to improve the quality of the timetables. It deals with the long-term and systematic concept of international long-distance passenger rail transport on the Prague – Bratislava / Vienna and back in the post-pandemic period. For this purpose, specific scientific methods are selected, which can be applied in order to rationalize and optimize train timetables.

This study investigates the relationship between changes in the frequency of dwell time delays and passenger flow characteristics and the frequency of railway service during the COVID-19 pandemic. To do so we make use of automatic passenger count data from commuter trains in Southern Sweden. Our findings show that the frequency of dwell time delays decreased under COVID-19 conditions compared to the two years prior, but dwell time delays did not cease to exist altogether. The improvement in dwell time performance is found to occur for delays of 30 s and larger, whereas the occurrence of delays up to 15 s increased. No decline in the service frequency under COVID-19 conditions was found. Overall an improvement in dwell time punctuality can be observed under COVID-19 conditions. The analysis, somewhat, points towards a reduction in peak passenger loads to be one of the factors associated with this improvement. This is, however, not the sole reason as dwell time punctuality is found to improve for all volumes of boarding passengers. The lower passenger demand thus improved dwell time punctuality under COVID-19 conditions, but it does not tell the whole story. When trying to improve dwell time punctuality it is thus not sufficient to only reduce the number of passengers boarding, but other measures are necessary as well.

To addreess the challenge of overcrowding in the urban rail transit system, this paper proposes a novel joint optimization strategy that optimizes the timetable and the passing facility's working status (PFWS) simultaneously according to the passenger demands. To this end, a mixed-integer nonlinear programming (MINLP) model is formulated to jointly minimize overcrowding on trains and platforms, as well as the passenger travel time. The passing facility setting and the passenger flow activities depiction are particularly taken into account by the rigorous constraints. Subsequently, we design a simulation-based hybrid variable neighborhood search (SHVNS) algorithm to efficiently generate near-optimal solution. This algorithm incorporates a variable neighborhood search (VNS) algorithm, a randomly reset strategy, and a simulation-based algorithm. The VNS algorithm includes five neighborhood operators to enhance search efficiency. Finally, various experiments with the real-world data from Chongqing rail transit line 6 in China are tested to prove the applicability and the performance of our proposed model and algorithm. The computational results show that the joint optimization strategy outperforms a current operation strategy in terms of the overcrowded situation on trains and platforms, often by more than 60%, and some management implications and theoretical support can be obtained for the urban rail transit operator. [ABSTRACT FROM AUTHOR]

University timetable scheduling, which is a typical problem that all universities around the world have to face every semester, is an NP-hard problem. It is the task of allocating the right timeslots and classrooms for various courses by taking into account predefined constraints. In the current literature, many approaches have been proposed to find feasible timetables. Among others, swarm-based algorithms are promising candidates because of their effectiveness and flexibility. This paper investigates proposing an approach to university timetable scheduling using a recent novel swarm-based algorithm named Spotted Hyena Optimizer (SHO) which is inspired by the hunting behaviour of spotted hyenas. Then, a combination of SA and SHO algorithms also investigated to improve the overall performance of the proposed method. We also illustrate the proposed method on a real-world university timetabling problem in Vietnam. Experimental results have indicated the efficiency of the proposed method in comparison to other competitive metaheuristic algorithm such as PSO algorithm in finding feasible timetables.

The main aim of this study was to develop a method for assessing the level of robustness of timetabled transport performance in rail transport. When the railway lines are supplied by DC networks, lower voltages are observed, and consequently, current values are often ten times higher than in AC networks. This is an operational problem, as high currents make it easier to overload the supply network. Based on a literature review, the authors show that the problem of running railway traffic when the capacity of the power supply network is limited (by the size of the permitted currents) is not well studied. The authors propose a method based on the Markov approach supplemented by classical theoretical vehicle traffic dynamics to improve the operational robustness of the rail transport system using DC power supply system. Each train run was parameterised in such a way that it is possible to determine the state that the train is in during the run, the transitions between states, and the determination of the probabilities of occurrence of such states. On the other hand, classical vehicle dynamics was used to assess the load generated by the train on the power grid. The proposed method—reduced to a function—was verified using a case study. The method of timetable reconfiguration proposed by the authors increased the operational robustness from 0.9454 to 0.9774. [ABSTRACT FROM AUTHOR]

Rapid transit systems play a significant role in supporting rapid social and economic development in large cities all over the world. However, the systems consume a large amount of energy, which brings increasing environmental concerns. A number of energy-saving technologies have been studied on railways. However, few of the outcomes have been tested and evaluated in practice. This paper presents the development of a timetable optimization and trial test on a metro line to reach the full potential of the train regenerative braking system. To achieve this purpose, a timetable optimization algorithm has been developed, and a trial test of the optimal timetable has been arranged on a metro line for a whole day. In the test, all the trains running in the network were organized to operate in accordance with the optimal timetable. The trial test results indicate that by applying the optimal timetable, the regenerative braking energy utilization can be improved, thereby reducing the overall network energy usage. [ABSTRACT FROM AUTHOR]

Faced with the integrated system composed of the train power system, the photovoltaic (PV) power system, and the energy storage system (ESS), this research studies the energy-efficient operation and energy management strategy from the perspective of both train optimal control and timetable optimization, aiming at achieving a long-term energy consumption reduction. A two-step approach for collaboratively optimizing the train timetable, speed trajectory, and energy management strategy considering the stochastic characteristics of PV power generation is proposed to solve this large-scale complex problem. Before the two-step approach, a mixed-integer linear programming (MILP) model is established to optimize the energy consumption of the inter-station operation. On this basis, explicit energy consumption expressions for all inter-stations of the entire line are obtained by the proposed data fitting method. The historical PV power data is clustered to generate scenarios with different probabilities to characterize the stochastic PV power. The first step of this two-step approach is to minimize the total energy consumption expectations of all inter-stations determined by the obtained explicit energy consumption expressions to optimize the timetable while ensuring the total time and time window constraints are met. The second step is to minimize the weighted sum of energy consumption under all possible scenarios to obtain the optimal speed trajectory and energy management strategy based on the optimized timetable obtained in the first step. The validity of the model is verified by case studies using the real data of Qingdao Metro Line 11 under both scenarios with and without PV power. This study provides a novel method for energy-efficient operation and energy management of the integrated system and demonstrates the prospect of the proposed two-step stochastic optimization in reducing the net grid-supplied energy for the long-term operation of urban rail transportation systems.

Quality and efficient long-distance transport as a key system of public passenger transport could be the basis for the national and international comprehensive integrated transport system. Especially due to the pandemic caused by the COVID-19 disease, the demand for long-distance transport has significantly decreased since March 2020 in the Slovak Republic on the busiest long-distance line Bratislava–Žilina–Košice. It is, therefore, necessary to propose various measures in order to increase this demand and bring passenger frequencies to at least the level of values before this period. This paper analyzes the impact of the measures on passenger frequencies in 2020, examining the amount of their fall in individual months of the first half of the year 2020 on the long-distance route Bratislava–Žilina–Košice. Furthermore, the paper deals with the long-term concept of national long-distance passenger rail transport on the mentioned line in the period after the end of the pandemic. It uses scientific methods enabling to rationalize and optimize current train timetables. The benefits of these proposals will be to offer passengers better transport services, with their frequencies expected to increase in the coming years. [ABSTRACT FROM AUTHOR]

Background: As a debilitating clinical condition, if Body Dysmorphic Disorder (BDD) is untreated will turn to a chronic illness. Therefore, the treatment of BDD is considered as an urgent clinical need. Aims: Introduction of the principles and techniques of a new psychotherapeutic model for the treatment of psychological disorders, shortly named PTC (Paradox + Timetable = Cure), is one of the objectives if this paper. Evaluating the effectiveness of PTC model for the treatment of BDD is the second objective. Method: The present study is an evidence-based clinical case study. The PTC therapy process and outcomes for a 33-year old woman suffering from BDD is fully described in the present article. Results: Results of a five-session PTC therapy for the patient indicated that the treatment outcomes were completely successful. A 24- and 36-month follow-up also revealed that the therapeutic changes were stable and continued during which no relapse was happened. Treatment outcomes for the patient confirm the deep and permanent effects of the PTC psychotherapeutic model in the shortest possible time for the treatment of BDD. The influential mechanisms of “paradoxical timetable” and its adjustment to the treatment outcomes of the patient are explained in the present article. Conclusions: The PTC psychotherapeutic model, as a very short-term, simple, effective, efficient, and yet economical approach is introduced and suggested for the treatment of BDD.

This paper presents a pricing model of railway infrastructure capacity allocation functioning as a regulatory measure while fulfilling the regulatory requirements on railway infrastructure capacity allocation. The prices of railway infrastructure capacity allocation will be modelled with regard to all economically justifiable costs of railway infrastructure capacity allocation. The structure of model has been developed as a set of calculation sheets in Microsoft Excel. The recommended prices for railway capacity have been found by simulation of a set of variants and the recommendation is done for different operational conditions in an individual way. It analyses different products offered by the railway infrastructure capacity allocator both in the annual working timetable mode, and in the individual ad hoc mode. The aim of the proposed model is to motivate not only railway undertakings, but also the railway infrastructure capacity allocator to submit requests for railway infrastructure capacity in the annual working timetable mode rather than in the individual ad hoc mode. The total price is then verified to the cost of railway infrastructure capacity allocation. This process then ensures the regulation of the demand of railway undertakings on the given route and can influence the decision about the use of the product offered.

Analysing transport timetables is an important task, as it brings the opportunity to discover which routes commonly lead to delays. Frequent pattern mining is a technique used to support such type of discovery. However, functional dependencies are intrinsic properties present in timetables, particularly related to attributes derived from the origin–destination matrix. Such functional dependencies compromise the search for patterns in timetables in both the number of association rules (ARs) generated and the computational cost. Several of these ARs refer to the same information. Redundancy removal techniques can reduce the number of ARs. However, these techniques are designed to be used after mining finishes, which increases the computational cost of finding useful ARs. This work presents timetable pattern mining (T‐mine), a novel method for frequent pattern mining that improves knowledge discovery in timetables. We evaluated T‐mine using Brazilian Flight Data and compared T‐mine with the direct application of frequent pattern mining approaches with and without functional dependencies. Our experiments indicate that T‐mine is about one order magnitude faster than other methods with functional dependencies. [ABSTRACT FROM AUTHOR]

This article discusses the scientific evaluation of a pilot project proposing a school time management measure allowing students who wish to leave the classroom to participate in music lessons given by professionals, or to benefit from special measures. This project, entitled "Supervised self-employment", should enable better management of school and extra-curricular activities through greater consideration and integration of the latter, as well as closer collaboration between the school and local cultural institutions. This article presents the perceptions of the different stakeholders induced by a reorganisation of the timetable. In this article, the research problem consists in answering the following research question: how do the different stakeholders perceive this reorganisation of the timetable in terms of reconciliation of in-school and out-of-school time, partnership and school justice ?. [ABSTRACT FROM AUTHOR]

Abstract The performance of the West Midlands Metro in the United Kingdom is analyzed in the present study by evaluating the existing timetables of the metro system. Using SIMUL8 computer software, a discrete event-based simulation prototype modeling the metro system is developed and implemented. The model adequately describes the performance of the West Midlands Metro system. By running simulations, the overall utilization level of the metro system is calculated. The results of the simulation model indicate that the metro system is being underutilized. The low utilization rates indicate a potential for the introduction of new services capable of exploiting the existing infrastructure and improving the utilization levels of the existing metro system; For example, the potential of using the current metro system for urban freight transport could be a new service of interest and provide scope for further research.

With the aim of supporting the process of scheduling a hybrid cyclic timetable and adapting traffic needs, this paper is concerned with inserting additional train paths problem for tactical and short-term planning applications with multiple objectives. Focusing on an existing cyclic timetable on a high-speed passenger rail line, the problem is to minimize both the total adjustments for initial trains and the number of required train-sets. The timetable scheduling, train-set planning and rescheduling are three complex optimization problems respectively and usually solved in a sequential manner. In this paper, these phases are integrated in a mixed integer programming model, and the multi-objective adding train paths (ATP) model is proposed, which decides simultaneously initial trains' modifications, additional trains' schedules and train-set circulation. The tolerance of disruption for initial trains including allowed adjustment and periodic structure is taken into account in light of the practical concerns. The difficulty of this integrated problem is that train-sets circulation is usually determined after all of the train lines and timetable have been fixed. However, in the adding train paths problem, the additional trains do not exist in the initial timetable. In order to solve the problem in a reasonable time, a relaxation approach to the adding paths problem is presented. We start from fixed train-set route, and then apply flexible train-set route that provides possible alternative turning activities to decrease the number of required train-sets. A case study based on Shanghai-Hangzhou high-speed rail line in China illustrates the methodology and compares the performance of various settings of perturbation tolerance, time window and train-set applications.

The efficient scheduling of train running is fundamental to operational planning of train movement in the passenger-based transportation industry. The timetable determines the availability of transport services across time & space. It also indicates the need of supporting infrastructures like rolling stock, train control system, traction system, and manpower. The rationalization of the timetable may profoundly affect the efficiency of the operator by optimizing the need for supporting infrastructure. Timetable rationalization in an urban rail transit system is considered with the two aims, first is human intervention to meet up the rising passenger demand in form of ridership. Second is lowering the operational expenditure in terms of energy consumption during train operation. A data-based exploratory case study of Delhi Metro line-2 is used to demonstrate the performance of the proposed approach. This paper presents an overview of the initiatives adopted in Delhi Metro Rail Corporation to ameliorate the train schedule and timetable by adopting innovative ways like matching supply with demand, real-time monitoring of demand for necessary intervention in the timetable of the day, coasting or energy-saving mode of operations in Automatic Train Operation, dwell time optimization, and interlacing of high-capacity trains during peak hours.

Planning in public transportation is traditionally done in a sequential process: After the network design process, the lines and their frequencies are planned. When these are fixed, a timetable is determined and based on the timetable, the vehicle and crew schedules are optimized. After each step, passenger routes are adapted to model the behavior of the passengers as realistically as possible. It has been mentioned in many publications that such a sequential process is sub-optimal, and integrated approaches, mainly heuristics, are under consideration. Sequential planning is not only common in public transportation planning but also in many other applied problems, among others in supply chain management, or in organizing hospitals efficiently.The contribution of this paper hence is two-fold: on the one hand, we develop an integrated integer programming formulation for the three planning stages line planning, (periodic) timetabling, and vehicle scheduling which also includes the integrated optimization of the passenger routes. This gives us an exact formulation rewriting the sequential approach as an integrated problem. We discuss properties of the integrated formulation and apply it experimentally to data sets from the LinTim library. On small examples, we get an exact optimal objective function value for the integrated formulation which can be compared with the outcome of the sequential process.On the other hand, we propose a mathematical formulation for general sequential processes which can be used to build integrated formulations. For comparing sequential processes with their integrated counterparts we analyze the price of sequentiality, i.e., the ratio between the solution obtained by the sequential process and an integrated solution. We also experiment with different possibilities for partial integration of a subset of the sequential problems and again illustrate our results using the case of public transportation. The obtained results may be useful for other sequential processes.

In this paper, the main problems of scheduling screenings for a cinema were considered. The activity of one cinema “X” is described and the restrictions that must be observed and taken into account when planning the schedule of sessions are analyzed. The solution to this problem is due to the complexity and time-consuming planning of the cinema schedule. To achieve this goal, the article analyzes the statistical data obtained in the cinema “X”. An analysis was carried out using the methods of statistical data analysis and predictive factors of movie attendance were identified, regression models of attendance were developed. Based on the developed regression models, statistical estimates of attendance predictive factors were obtained. Taking into account the results obtained, an optimization mathematical model for the formation of a rental schedule has been developed, which makes it possible to increase the box office of a cinema.

University timetable scheduling, which is a typical problem that all universities around the world have to face every semester, is an NP-hard problem. It is the task of allocating the right timeslots and classrooms for various courses by taking into account predefined constraints. In the current literature, many approaches have been proposed to find feasible timetables. Among others, swarm-based algorithms are promising candidates because of their effectiveness and flexibility. This paper investigates proposing an approach to university timetable scheduling using a recent novel swarm-based algorithm named Spotted Hyena Optimizer (SHO) which is inspired by the hunting behaviour of spotted hyenas. Then, a combination of SA and SHO algorithms also investigated to improve the overall performance of the proposed method. We also illustrate the proposed method on a real-world university timetabling problem in Vietnam. Experimental results have indicated the efficiency of the proposed method in comparison to other competitive metaheuristic algorithm such as PSO algorithm in finding feasible timetables. [ABSTRACT FROM AUTHOR]

Background: The principles and techniques of a new psychotherapeutic model for the treatment of psychological disorders, shortly named PTC (Paradox + Timetable = Cure), is introduced in this article. Aims: Evaluating the effectiveness of PTC model for the treatment of Social Anxiety Disorder (SAD) is another objective of the present article. Method: PTC is a very short-term psychotherapeutic model successfully used for the treatment of a wide range of psychological disorders including anxiety disorders, obsessive-compulsive and related disorders, trauma- and stress-related disorders, somatic symptom and related disorders and feeding and eating disorders (Besharat, 2017). The PTC therapy process and outcomes for a SAD patient is fully described in the present article. Results: Results of a three-session PTC therapy indicated that the treatment of the patient was successfully done. The result of a three-years follow-up showed that the therapeutic changes were satisfactory, stable and permanent, during which no relapse was happened. These results corroborated the deep and permanent effects of the PTC psychotherapeutic model in the shortest possible time. The influential mechanisms of “paradoxical timetable”, as the main PTC technique, and its adjustment to the treatment outcomes of the patient are also explained in the present article. Conclusion: The PTC psychotherapeutic model, as a very short-term, effective, efficient and yet economical approach is introduced and suggested for the treatment of SAD.

The INFODORADCA+ project was one of the biggest and most complicated undertakings referring to the labour market, including the development of 1000 professions. It was a challenge from the point of view of the methodology and importance for the labour market institutions but also from the perspective of managing the whole process. The project was implemented by five different institutions representing both state-owned research institutes and private companies. All of them were fully responsible for the components of the project assigned to them; on the other side, the management team had to introduce unified procedures that enabled control and management of the project’s team, quality, costs and risks. In total, some seven thousand experts were involved in the project; vast majority of them were engaged using time-consuming (and unified) contracting procedures. In addition, there were hundreds of stakeholders also involved in the process. The project’s success was based on the combination of “soft” management measures, respecting the project’s partners autonomy and based on consensus building with the implementation of obligatory procedures, forms and checklists, binding for all the Partners.

The organization of education for persons who are studying is carried out in accordance with the courses timetabling. Courses timetabling should provide an effective implementation of the curriculum in full. The problem of creating the courses timetabling has been given sufficient attention during the last decades. But even today, the process of creating the courses timetabling requires a fairly large part of human control. The typical problem of creating the courses timetabling is to plan a set of meetings between teachers and students over a period of time that requires some resources and should meet some additional requirements. Significant requirements in scheduling are those in which the teacher, student, or audience is not used more than once at the one-time interval. Creating the courses timetabling in institutions of higher education is carried out every semester. Preparing the timetabling of the courses is a labor-intensive, tedious process that requires a significant amount of human resources and time. In this scientific article, an analysis of process creation of the courses timetabling is carried out. In the course of work are investigated basic guidance documents for the creation of the courses timetabling. On the basis of controlled observation, where the observer was included in the process and conducted in real conditions, on the basis of the dispatch of educational department of the Odessa National Academy of Food Technologies, the process of creation of the courses timetabling is described, and the main structures of the institution of higher education, which are involved, are determined. On the basis of controlled observation, where the observer was included in the process and conducted in real conditions, on the basis of the dispatch section of educational department of the Odessa National Academy of Food Technologies, the process of creation of the courses timetabling is described, and the main structures of the institution of higher education, which are involved, are determined. Constraints which must be observed during the process are divided into hard and soft. Actual solutions are investigated, such as: genetic algorithm, greedy algorithm, graph coloring method, method of logical programming with constraints, etc. Describes what determines the performance of these methods and algorithms.

Modern trams typically run along semi-exclusive right-of-way. Although tram lanes isolate trams from other traffic in the running sections, the operation process will be affected by signal control. To improve the service quality of trams and reduce the negative impact on intersections caused by bidirectional priority requests, we propose a timetable optimization method for a single two-way tram line based on active transit signal priority strategy. Combining with the characteristics of bidirectional signal priority strategy, trams can pass through the intersections without stopping by adjusting the running times and dwell times. A multiobjective optimization model of a tram timetable is established to minimize the total travel time, dwell time increment, and negative effect of the signal priority strategy. For obtaining a timetable with equal satisfaction for the three objectives, we adopt the fuzzy mathematical programming approach to transform the problems into mixed integer linear programming (MILP) problems, which can be solved by using standard solvers. The case study of Nanjing Qilin Tram Line 1 shows that the timetable optimization method designed in this paper can effectively improve the service efficiency of trams, and reduce the negative impact of the signal priority strategy on social vehicles. These empirical findings can give us some useful insights on the optimum design of tram timetable.

The main aim of this study was to develop a method for assessing the level of robustness of timetabled transport performance in rail transport. When the railway lines are supplied by DC networks, lower voltages are observed, and consequently, current values are often ten times higher than in AC networks. This is an operational problem, as high currents make it easier to overload the supply network. Based on a literature review, the authors show that the problem of running railway traffic when the capacity of the power supply network is limited (by the size of the permitted currents) is not well studied. The authors propose a method based on the Markov approach supplemented by classical theoretical vehicle traffic dynamics to improve the operational robustness of the rail transport system using DC power supply system. Each train run was parameterised in such a way that it is possible to determine the state that the train is in during the run, the transitions between states, and the determination of the probabilities of occurrence of such states. On the other hand, classical vehicle dynamics was used to assess the load generated by the train on the power grid. The proposed method—reduced to a function—was verified using a case study. The method of timetable reconfiguration proposed by the authors increased the operational robustness from 0.9454 to 0.9774.

Rapid transit systems play a significant role in supporting rapid social and economic development in large cities all over the world. However, the systems consume a large amount of energy, which brings increasing environmental concerns. A number of energy-saving technologies have been studied on railways. However, few of the outcomes have been tested and evaluated in practice. This paper presents the development of a timetable optimization and trial test on a metro line to reach the full potential of the train regenerative braking system. To achieve this purpose, a timetable optimization algorithm has been developed, and a trial test of the optimal timetable has been arranged on a metro line for a whole day. In the test, all the trains running in the network were organized to operate in accordance with the optimal timetable. The trial test results indicate that by applying the optimal timetable, the regenerative braking energy utilization can be improved, thereby reducing the overall network energy usage.

This work considered a joint problem of train rescheduling and closure planning. The derivation of a new train run schedule and the determination of a closure plan not only must guarantee the satisfaction of all the given constraints but also must optimize the number of accepted closures, the number of approved train runs, and the total time shift between the resultant and the original schedule. Presented is a novel nonlinear mixed integer optimization problem which is valid for a broad class of railway networks. A multi-level hierarchical heuristic algorithm is introduced due to the NP-hardness of the considered optimization problem. The algorithm is able, on an iterative basis, to jointly select closures and train runs, along with the derivation of a train schedule. Results obtained by the algorithm, launched for the conducted experiments, confirm its ability to provide acceptable and feasible solutions in a reasonable amount of time. [ABSTRACT FROM AUTHOR]

Urban rail transit networks seldom provide 24-hour service. The last train is the latest chance for passengers. If passengers arrive too late to catch the last train, the path becomes inaccessible. The network accessibility thus varies depending on the departure time of passenger trips. This paper focuses on the computation method on the time-dependent accessibility of urban rail transit networks in order to facilitate the itinerary planning of passengers. A label setting algorithm is first designed to calculate the latest possible times for Origin–Destination (O–D) pairs, which is the latest departure times of passengers from the origins such that the destinations can be reach successfully. A searching approach is then developed to find the shortest accessible path at any possible departure times. The method is applied in a real-world metro network. The results show that the method is a powerful tool in solving the service accessibility problem. It has the ability to allow passengers to plan an optimal itinerary. Comparison analysis indicates that the proposed method can provide exact solutions in much shorter time, compared with a path enumeration method. Extensive tests on a set of random networks indicate that the method is efficient enough in practical applications. The execution time for an O–D pair on a personal computer with 2.8 GHZ CPU and 4GB of RAM is only 1.2 s for urban rail transit networks with 100 transfer stations.

This contribution in a cross section way focused on the analytical determination of practical capacity of main tracks and the issue of the required capacity in the context of the comparison of national methodology used by the ŽSR and the recommended international UIC methodology. Methodology for the calculation of permeable performance within the national conditions is stipulated by ŽSR´s regulation – D24, the methodology within the international conditions for members of the UIC railway union is recommended by UIC Code 406. Both of presented methodologies have their pros and cons, which are consistently derived from this text.

The article presents issues concerning rail transport (rail, metro and tramway) and factors influencing the planned implementation of the schedule. At the beginning, the scope of application of the robustness concept was analysed, based on scientific and industry literature. Then the attention was focused on the model of the rail transport system and the schedule, the basic indicator of robustness assessment was discussed, taking into account the methods of analysis used and many variables occurring in rail transport. Finally, a review of the state of knowledge is summarised and the most important observations from the analysis are indicated. In the case of a robust schedule there is no propagation of disruption across the network after an adverse event has occurred. [ABSTRACT FROM AUTHOR]

The optimization of train trajectory and timetable offers two effective methods of energy-efficient operations. Most traditional research optimizes them separately and thus the global optimality cannot be achieved. Previous work has mainly concentrated on minimizing the mechanical energy consumption of trains, not the electrical energy. This paper aims to develop an integrated model to optimize the integrated timetable, which includes both the timetable and the train trajectory achieve the minimum electrical energy consumption. The AC power supply system model is first proposed to calculate the parameters of the AC power supply network. Then, a model is developed to calculate various energy consumptions using power flow calculation. Furthermore, an integrated timetable optimization model for minimum total energy consumption of AC railway system is proposed and the optimal integrated timetable is obtained by the proposed hybrid GA-PSO algorithm. Finally, 5 real-world case studies based on the Lanzhou–Xinjiang high-speed railway are presented. The results show that the proposed integrated model can achieve a reduction in total energy consumption for the entire line up to 14.3% compared with the previous optimization model. The hybrid GA-PSO algorithm achieves the best results compared with the results achieved by the GA and PSO algorithms applied along. [ABSTRACT FROM AUTHOR]

The performance of the West Midlands Metro in the United Kingdom is analyzed in the present study by evaluating the existing timetables of the metro system. Using SIMUL8 computer software, a discrete event-based simulation prototype modeling the metro system is developed and implemented. The model adequately describes the performance of the West Midlands Metro system. By running simulations, the overall utilization level of the metro system is calculated. The results of the simulation model indicate that the metro system is being underutilized. The low utilization rates indicate a potential for the introduction of new services capable of exploiting the existing infrastructure and improving the utilization levels of the existing metro system; For example, the potential of using the current metro system for urban freight transport could be a new service of interest and provide scope for further research. [ABSTRACT FROM AUTHOR]