Towards Cyclic Scheduling of Grid-Like Structure Networks

Cyclic scheduling problems arise in a variety of transportation applications and service domains. Within the class of those problems we can identify situations where there is need to make use of different modes of transportation. What is of particular interest in this paper is the design of a class of multimodal cyclic processes (MCP) for production engineering and supply chains. The paper presents a new modeling framework enabling to prototype and evaluate multimodal processes while comparing their cyclic steady states. A way in which the multimodal processes encompass the behavior of supporting them concurrently flowing cyclic processes (SCCP) is discussed in terms of constraints satisfaction problem. Possible implementations are illustrated on example of the flexible manufacturing system operation.KeywordsCyclic processesCyclic schedulingConcurrent processesMultimodal processesState spaceDeclarative modelingDispatching rules

Introduc tion. Space-planning solutions for underground stations have an effect on the comfort and safety of passengers. Mathematical modelling is a perspective method for solving problems dealing with the determination of adequacy of adopted space-planning solutions for stations depending on passenger traffic. Aims and purpo ses. The purpose of the study is to justify the method of mathematical modelling of passenger flows to develop optimal space-planning solutions of interchange stations of underground. To achieve this goal, the following tasks were solved: the development of a model interchange station concept; modelling passenger flows with initial and optimized volume planning solutions; modelling of passenger evacuation from the station in case of fire in the basement of the arriving train’s central carriage. Methods. The paper presents a method of mathematical modelling to justify the space-planning solutions of underground stations. The software package Pathfinder developed an individual flow model of the interchange station, which simulated the passenger flows with initial and optimized volume-planning solutions. The software package PyroSim was used to simulate the spread of fire hazards. Result s and discussion. Based on the results of mathematical modelling, the optimal space-planning solutions for underground stations were determined, on the basis of which the passenger evacuation scenario was performed. It is obtained that there are 3,684 passengers and 296 workers at the station when the evacuation begins. The simulation results showed that the total estimated evacuation time from a typical transfer station is 814 seconds . It is obtained that the values of dangerous fire factors in the calculated points do not reach critical values until the evacuation is completed. Co nclusions. A mathematical model of a typical interchange station has been developed and implemented to determine the optimal space-planning solutions and calculate the safe evacuation of people. On the basis of this study in the new edition of the Code of Practice 120.13330.2022 “Underground” made amendments that determine that the estimated number of passengers evacuating from the station in case of fire, is based on mathematical modelling of passenger traffic during the rush hour.

As the passenger flow distribution center cooperating with various modes of transportation, the comprehensive passenger transport hub brings convenience to passengers. With the diversification of passenger travel modes, the passenger flow scale gradually increases, which brings significant challenges to the integrated passenger hub. Therefore, it is urgent to solve the problem of early warning and response to the future passenger flow to avoid congestion accidents. In this paper, the passenger flow GRNN prediction model is proposed, based on the K-means cluster algorithm, and an improved index named BWPs (Between-Within Proportion-Similarity) is proposed to improve the clustering effect of K-means so that the clustering effect of the new index is verified. In addition, the passenger flow data are studied and trained by combining with the GRNN neural network model based on parameter optimization (GA); the passenger flow prediction model is obtained. Finally, the passenger flow of Chengdu East Railway Station has been taken as an example, which is divided into 16 models, and each type of passenger flow is predicted, respectively. Compared with the traditional method, the results show that the model can predict the passenger flow with high accuracy.

The transports’ infrastructure represent a key element for the economic growth of both regions and sectors in Italy. In order to better examine it, we go through the analysis of passenger traffic making a distinction among modes of transport: railway, airport, road and sea. The study gives also a statistical overview on accidents related to the different means of transport; where the number of road accidents, despite its decline, remains very high. The paper concludes with recommendation toward strategies to implement security, particularly in those areas disadvantaged, as the Mezzogiorno.

This paper presents the results of a quantitative study in the Czech Republic to understand travellers’ attitudes towards and motivation to use different means of transport. Two Czech cities, Olomouc and Ostrava, are compared from the point of view of factors influencing spatial and temporal patterns and citizen’s selection of transport mode and transport behaviour (range and daily movements of the population, perception of the quality of public transport etc.). The data for the analysis were obtained from the survey with more than 500 respondents in each city. Spatial and temporal behaviour represented by the pattern of the movement in Olomouc and Ostrava city was identified by statistical and visual analytics methods. Based on a case study of two cities of a different size, we conclude that the size and shape of the city centre (spatial structure) influence not only the distances travelled but also the average speed of public transportation (slower for a smaller city). Distances and choice of transport mode also vary with the density of urban areas but can also be influenced by the spatial structure of the city. The walking distance to a public transport stop does not influence the most frequently used mode of transport. Temporal patterns in both cities are very similar and are not dependent on city size or city spatial structure. The spatial patterns of the car and public transport flows are similar in both cities. Different patterns can be observed for walking and shopping routes.

As more and more large-scale winter events are held in different areas, a reasonable configuration of service facilities is crucial for ensuring the successful execution of these events. Based on an analysis of the passenger flow for large-scale events in outer suburbs, this study has developed a dynamic evolution model to well simulate passenger arrival distribution among nodes and queue performance over time. Subsequently, an optimization model for service facility configuration based on node linkage is proposed. Using a large-scale winter event as a case study, we conclude that assigning a higher objective weight to spectators’ queuing time cost in the optimization model leads to an increase in the number of configured service facilities among nodes, thereby enhancing service quality. Different facility layouts for security checks and ticket checks have no significant effects on the optimal number of configured service facilities and spectator queuing time costs. However, implementing a remote security check can alleviate passenger congestion at downstream nodes and reduce the overall queuing time cost. The dynamic evolution model and the service facilities configuration model are suitable for coordinating passenger flow under limited-service facility provision along with measures such as adjusting facility layouts and controlling passenger flow. Thus, a good match between passenger flow distribution and facility service capacity can be achieved. The research conclusions can provide a reference for the analysis of passenger flow, service facility configuration, and passenger flow organization for large-scale events held in the outer suburbs.

The article is devoted to methodological features of forecasting intercity passenger flows under the conditions of transformation of the transport system of Russia, namely, the emergence of a new type of rail transport which is high-speed rail. The objective of the article is to present the authors’ methodology for forecasting passenger flows and to prove its higher efficiency relative to the methods used in Russia today. The article considers the historical aspect of forecasting passenger flows, analyzes strengths and weaknesses of existing approaches to forecasting and modelling passenger flows. The authors argue that it is impossible to simulate the number of trips with changes in transportation parameters only on the basis of patterns identified by retrospective data series (the most common approach to forecasting passenger flows in Russia). The article proposes an alternative methodology based on the calculation of passenger’s total costs of a trip, which depend on cost of travel, loss of time, frequency of departure of vehicles and their comfort, as well as considering the dynamics of key social-economic indicators. The technique allows minimizing measurement errors arising from the lack of primary information about some types of passenger transport, as well as calculating the induced demand for trips arising as a result of improved transportation characteristics. The authors identified and expressed in quantitative terms the main factors of redistribution of passenger flows to newly introduced types of transport. The article discusses the experience of forecasting passenger flow according to the proposed method at the example of four itineraries where movement of high-speed trains of Lastochka type started. The forecasted results are compared with the actual volumes of transportation, on the basis of which conclusions are drawn about the effectiveness of the forecasting method and its applicability in modern realities of the Russian transport system. The advantages and disadvantages of the proposed approach to forecasting passenger traffic, as well as the possibilities of its implementation and further development in Russia are identified.

This paper describes a Grid-like Material Transportation Network (GMTN) in which several heterogeneous means of transportation (Automated Guided Vehicles (AGVs), hoists, lifts, etc.) interact with each other via common shared workstations to provide a variety of demand-responsive material handling operations. Different material handling transport modes provide movement of workpieces between workstations along their manufacturing routes in the GMTN and they can be seen as processes realized with synergic utilization of various local periodically acting unimodal processes. The main contribution of this research is the solution of a constraint satisfaction problem addressing AGVs fleet match-up scheduling subject to GMTN and fuzzy operation time constraints. In the presented case both production rate (production takt) and operations execution time are described by imprecise (fuzzy) data. In other words, the research’s objective concerns assessing grid-like networks of periodically acting local transportation modes from the perspective of possible mass-customized oriented requirements imposed on scheduling of multimodal flows of jobs assigned to certain technological routes passing through common shared workstations.

Inferring dynamic origin-destination flows by transport mode using mobile phone data

The tasks of transport planning are relevant for most countries and comprise implemenation of solutions at regional and local level. The development of transport planning documents in the constituent entities of the Russian Federation is an acute problem and implies the achievement of such goals as improving the quality of passenger transportation and reducing transportation costs. Each of the transport planning documents includes a list of measures, the implementation of which improves the quality of passenger service and the efficiency of the use of rolling stock. The objective of the article is to determine the significance of the influence of technical and operational factors on the resulting indicators of passenger service quality and efficiency of rolling stock use. The research applied experiment planning method described in the work of Yu. P. Adler. The experiment planning method used makes it possible to obtain quantitative estimates of the influence of factors with the same reliability as with other methods. The evaluation was carried out for independent or conditionally independent factors. In the researched case, such factors comprise the number of buses on the route, the length of the route, the turnaround time, the downtime at the terminal points, the allowable deviation from the schedule, the work hours of the drivers, the zero mileage of all buses. Constants in the calculations are independent factors related to the characteristics of the demand for transportation, since when carrying out measures to improve the organisation of the work of buses on routes, they cannot be influenced. These factors comprise the walking distance on the route, the average travel distance of a passenger on the route and the passenger flow on the most loaded haul. The method is implemented in the article on the example of an operating bus on the route. For all basic factors, the upper, lower, and main levels are set. Based on the analysis of the actual values of technical and operational indicators on the existing routes of Moscow region, the numerical values of the above levels were determined. Next, the variation intervals for each factor were selected. An experiment in which all possible combinations of factor levels are implemented is known as a full factorial experiment. The coefficients calculated from the results of the experiment indicate the strength of the influence of a factor. The value of the coefficient corresponds to the contribution of this factor to the value of the optimisation parameter when the factor moves from the zero level to the upper or lower one. As a result of the research, it was found that five basic factors influence the time spent by a passenger, travel comfort, and the completeness of revenue collection, and ten factors affect the daily costs of servicing the route for a carrier. The specificity of the problem is that for all four optimisation parameters, one and the same matrix can be constructed. To conduct a full factorial experiment with varying ten factors at two levels, it is necessary to carry out more than a thousand calculation options. However, in accordance with the methodology, in this case, we can limit ourselves to the minimum number of calculations. On this basis, an experiment planning matrix was built, then, based on the results of calculations, the coefficients in the regression equations for each of the optimisation parameters can be determined. The regression coefficients obtained when calculating the experiment design matrix are similar to those that could be obtained as a result of calculations using the least squares method. Based on this, it is possible to calculate all the statistical characteristics of the basic factors necessary to determine the closeness of the relationship between the factors and optimisation parameters, as well as between the factors themselves. The experiment planning method used in the study made it possible to identify the factors influencing each of the four optimisation parameters. Therefore, the explicit dependence of the optimisation parameters on such a factor as the number of buses on the route was confirmed, but at the same time, the factors were ranked according to the degree of their influence on the result. The correspondence of the obtained results to real and obvious dependencies has allowed to conclude that the chosen method and its implementation are correct.

Mobility planning is rarely individually tailored. Instead people have to make an active effort to adapt standard solutions to their requirements. Routing apps like Google Maps allow for personalization only by saving important places like home and a workplace but do not allow the user to influence the routing suggestions or choice of mode of transport based on preferences, limitations, or situation. It becomes even more difficult when different means of transport are to interact since most routing applications offer very little multimodal optimization aside from the last mile. Thus, the objective of this article is to present a concept for the utilization of artificial intelligence and regression models in order to enable individual and sustainable mobility planning. To achieve this objective, initially existing routing and mobility planning applications are examined and are conceptually expanded in order to outlay the benefits of personalized route planning. The concrete objective alongside with a method for the development of a new solution is summarized. An algorithm fulfilling these objectives based on multiple linear regression is conceptualized. Relevant factors with coefficient are identified, as well as necessary data sources and interfaces. This algorithm is then implemented in a limited prototype as a proof of concept. Finally, this prototype is tested based on a set of mobility scenarios in order to validate the achievement of the defined objective.

VIVER -- A Sustainable Transport Vision for Germany

The paper concerns cyclic scheduling problems arising in a Multimodal Transportation Network (MTN) in which several unimodal networks (AGVs, hoists, lifts, etc.) interact with each other via common shared workstations as to provide a variety of demand-responsive material handling operations. The material handling transport modes provide movement of work-pieces between workstations along their manufacturing routes in the MTN. The goal is to provide a declarative framework enabling to state a constraint satisfaction problem aimed at AGVs fleet match-up scheduling taking into consideration assumed itineraries of concurrently manufactured product types. In that context, treating the different product types as a set of cyclic multimodal processes is the main objective to discuss the conditions sufficient for FMS rescheduling imposed by production orders changes. To conclude, the conditions sufficient for an FMS rescheduling imposed by changes of production orders treated as cyclic multimodal processes are stated as the paper’s main contribution.

PurposeThis paper aims to analyze the demand for mobility in higher education to understand the critical elements of students' mobility and the potential impact of accessing sustainable alternatives. The demand for different means of transportation accounts for socioeconomic variables such as household income and size, gender, age, among other travel factors such as distance, time, speed and direct cost.Design/methodology/approachThis research uses a unique data set encompassing a representative sample of households across gender and municipalities in the Monterrey Metropolitan Area in Mexico. This paper uses the value of transportation time savings approach to estimate the derived demand for mobility in higher education across different means. The empirical strategy uses a linear utility framework in a multinomial non-ordered logit model to analyze the conditional selection of transportation as a function of sociodemographics, direct monetary costs and travel determinants such as travel time, distance and speed.FindingsMen students are more likely to use an unsustained transportation mode such as a car or cab than women. Income is a crucial determinant for transportation demand. There is a negative relationship between household income and walking or riding the bus but positive with driving a car. An increase in the time of the trip decreases the probability of walking while increasing the likelihood of using a car or riding the bus to school. Students who feel safe while riding a bus are more likely to use the bus or walk as transportation than using a car. Finally, having access to better quality sidewalks significantly incentive walking over other transportation options.Practical implicationsResults show that individuals would almost always choose private vehicles because of the personal comforts and time savings.Social implicationsUnderstanding the demand for higher education and access to sustainable transportation might provide new insights into campus planning and development. Access to public transportation options can reduce the travel costs for students with lower incomes and enlarge options for students who have to commute longer distances by car. Sustainable transportation access plays a role in promoting equality and economic development.Originality/valueThis study’s results bring new light on how transportation becomes an essential component of the opportunity cost of college education and could define its role in promoting equality or increasing inequality. This study’s finding is of particular interest for cities where housing location seems to be independent of access to school, work or other amenities.

Time-sensitive parcel deliveries—shipments requested for delivery in a day or less—are an increasingly important aspect of urban logistics. It is challenging to deal with these deliveries from a carrier perspective. These require additional planning constraints, preventing the efficient consolidation of deliveries that is possible when demand is well known in advance. Furthermore, such time-sensitive deliveries are requested to a wider spatial scope than retail centers, including homes and offices. Therefore, an increase in such deliveries is considered to exacerbate negative externalities, such as congestion and emissions. One of the solutions is to leverage spare capacity in passenger transport modes. This concept is often denominated as cargo hitching. While there are various system designs, it is crucial that such a solution does not deteriorate the quality of service of passenger trips. This research aims to evaluate the use of mobility-on-demand (MOD) services that perform same-day parcel deliveries. To test the MOD-based solutions, we utilize a high-resolution agent- and activity-based simulation platform of passenger and freight flows. E-commerce demand carrier data collected in Singapore are used to characterize simulated parcel delivery demand. We explore operational scenarios that aim to minimize the adverse effects of fulfilling deliveries with MOD service vehicles on passenger flows. Adverse effects are measured in fulfillment, wait, and travel times. A case study on Singapore indicates that the MOD services have potential to fulfill a considerable amount of parcel deliveries and decrease freight vehicle traffic and total vehicle kilometers travelled without compromising the quality of MOD for passenger travel. Insights into the operational performance of the cargo-hitching service are also provided.