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Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The period of Covid -19 pandemic unlocked many lessons and opened up the need to benchmark various interventions in the social setup, more so, the means to manage social services like education. Education is a right enshrined in article 26 (1) of the 1948 United Nations Human rights Declaration, and the Constitution of the Republic of Uganda (1995), particularly articles 30, 34(2) and objective XVIII. Uganda's Vision 2040 asserts that, the education curriculum, examination and instruction methods should always be revised to suit the proposed changes in the education system as well as being responsive to the global demands. The COVID-19 lockdown which took almost two years, introduced non-formal learning through use of internet, radios and televisions but these did not favor rural settings. In Uganda, 55.2 percent of households have radios, 7.2 percent own televisions while 19 percent can access internet with ease. Basing on participatory action design laid on the social learning framework the assumption is that data becomes information only when filtered through a theory of reality that common data is set on the policy environment, yielding diverse political strategies and holding distinct practical programs for implementation if interpreted through different value filters. This intriguing reality led us to visit 25 out of 30 Local Council (LC) one (1) Chairpersons in Kyotera and Kasaali Town Councils and found that each received one copy of learning materials which could be accessed through photocopying yet 10 percent of the beneficiaries could comply. To address the challenge and using these materials, we organized a total of 168 audio lessons for primary one to six; and senior one to three classes which we recorded and saved on memory sticks. We drew a timetable of three hours a day throughout a week and louder speakers were mounted in 11 most rural villages in Kyotera District to deliver lessons. Through interviews conducted on visit of at least one home from a village and from political leaders, testimonies showed that learning took place. Head teachers interviewed [4] also confirmed the same We concluded that through recorded audio lessons, content can well be delivered at any time. We recommend that; Governments, institutions, teachers and other facilitators, should adopt the model to extend learning to beyond classrooms with audio lessons for future use in learning and revisions. This can be through transmission of lessons on simple memory sticks and discs. Stakeholders at all levels of education should be encouraged to appreciate existence of pre- developed lessons and lectures which Amy not require internet connection by teachers - Government Organizations should use the model and fund extension of learning in rural villages in order to affirmatively have all learners supplement on learning obtained from classrooms. [ABSTRACT FROM AUTHOR]

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.

It has been pointed out that robotic surgery is more time-consuming than laparoscopic surgery, and a major challenge for the future is educating young surgeons while maintaining the surgical quality. To solve these problems, we report a role-sharing surgery (RSS) approach in which the surgery is divided into several areas and timetabled, with roles shared by several operators. We performed RSS for 19 standard colorectal cancer surgeries. The surgery was completed within + 28 min of the scheduled operation time, and a beginner robotic surgeon (BRS) was able to perform approximately 66% of the total surgery. There were no statistically significant differences in the short-term outcomes between the RSS and conventional surgery groups. Based on these findings, RSS has the potential to be the best practice for educating BRSs in robotic surgery, the use of which is expected to increase steadily in the future. [ABSTRACT FROM AUTHOR]

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.

Typically, the problem of scheduling exams for universities aims to determine a schedule that satisfies logistics constraints, including the number of available exam rooms and the exam delivery mode (online or paper-based). The objective of this problem varies according to the university’s requirements. For example, some universities may seek to minimize operational costs, while others may work to minimize the schedule's length. Consequently, the objective imposed by the university affects the complexity of the problem. In this study, we present a grouping-based approach designed to address the problem of scheduling the exam timetable. The approach begins by profiling the courses’ exams based on their requirements, grouping exams with similar requirements to be scheduled at the same time. Then, an insertion strategy is used to obtain the exam schedule while satisfying the imposed constraints of the targeted university. We applied this approach to the problem of exam scheduling at Al-Hussein Bin Talal University in Jordan and achieved a balanced exam schedule that met all the imposed constraints. [ABSTRACT FROM AUTHOR]

Copyright of Riwayat: Educational Journal of History & Humanities is the property of Riwayat: Educational Journal of History & Humanities and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

Forming university exam schedules in Southern Africa has always been difficult. It is a scheduling problem with strict rules (hard constraints) and flexible ones (soft constraints). Students must take a final exam for most courses they are enrolled in each semester, held in a supervised setting. Therefore, finding a suitable time and location for each student is a common challenge. This paper proposes a solution to this scheduling problem based on the behaviour of bees, using a model called BSet, which uses simulated robotic devices to find and schedule courses. The results show that this approach is efficient and effective in creating exam schedules. [ABSTRACT FROM AUTHOR]

Train timetable during the end-of-service period is crucial for passenger accessibility and operation cost in urban rail transit networks. Existing studies have investigated the last train timetabling problem for improving passenger accessibility. This study investigates a train timetabling problem for the end-of-service period, which concentrates on the coordination of the service ending time on different lines and the last several train timetables. A mixed-integer linear programming model based on a space–time network is proposed to determine the number of train services provided in the end-of-service period while coordinating the timetables of both last and non-last trains, of which the objective function minimizes the number of inaccessible passengers and operation costs. To address the computational challenges, a Benders decomposition algorithm is developed and enhanced with dedicated acceleration strategies. A dual solution algorithm is proposed to efficiently generate the optimal dual solution of the subproblems. A reformulation and update strategy is proposed for the Benders cuts, and a relax-and-fix heuristic is developed to improve solving efficiency of the master problem. Small-scale numerical experiments demonstrate the optimality and efficiency of the proposed Benders decomposition algorithm. Large-scale experiments in the Wuhan network show that the proposed model and algorithm can improve passenger accessibility by 6.8% without additional operation cost, and by 38.7% with a 28.4% increment in operation cost. • A train timetabling problem for the end-of-service period is investigated to determine the service ending time and trains' departure time. • A MILP model based on a space–time network is proposed to optimize the balance between passenger accessibility and operational costs. • A Benders decomposition algorithm is designed and enhanced with several acceleration techniques. [ABSTRACT FROM AUTHOR]

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]

One important benefit of air and high-speed railway (AH) integration services is increasing the number of destinations within passengers' reach, which means intermodal services can facilitate passengers from cities that are linked to nearby airports by railway, to travel to or from more locations. However, certain origin-destination (OD) pairs are not accessible when the flight and train timetables are not well coordinated, which will lead to a reduction in the overall benefit. Given the original timetables, a joint optimization model for flight and train timetables is proposed, to improve the intermodal service accessibility in an AH transfer hub with a railway link. The objectives are to maximize the weighted sum of accessible OD pairs and minimize the time shifts compared with the original timetables. A real-world case study in China is performed to demonstrate the applicability of the model. The results illustrate that the model can effectively improve the accessibility. [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]

In the luxury car showroom construction project in Jakarta, there was a delay in the floor installation work, where in the 10th week it was previously planned that the work performance would reach 100% but in fact it was only at 70.87%. The construction of this luxury car showroom project is planned to be completed within 10 weeks at a cost of Rp. 3,108,807,011 and with the limited time and cost, it is absolutely necessary to have proper, efficient and mature control. By referring to knowledge base management, namely project integration management from PMBOK sixth edition references and also from relevant journals, this study aims to dissect and determine the time and cost performance or performance, time and cost estimation predictions until the project is completed using the Earned method. Value Analysis is applied based on data obtained from the project such as work schedules, budget plans, work achievement reports, and actual costs that have been incurred. From the results of the analysis, it was found that the CPI value was 1.276 which with CPI> 1 means that there is no cost overrun and the SPI value is 0.996 which with SPI <1 indicates a delay. However, this EVA method is not appropriate to be used to evaluate work which includes procurement and installation because the difference in weight between the two types of work is too large. [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.