Готові списки джерел за темами / Bus lines Employees Timetables

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Добірка наукової літератури з теми "Bus lines Employees Timetables"

Автор: Grafiati
Опубліковано: 4 червня 2021
Оновлено: 19 лютого 2022

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Статті в журналах з теми "Bus lines Employees Timetables"

1

Wu, Yinghui, Yifan Zhu, and Tianyu Cao. "Mathematical Analysis and an Exact Solution Combined with Preprocessing Method for Resynchronizing of Bus Timetable Problem." Mathematical Problems in Engineering 2018 (September 23, 2018): 1–10. http://dx.doi.org/10.1155/2018/7832638.

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Анотація:
Bus timetabling is a subproblem of bus network planning, and it determines departure time of each trip of lines to make vehicles from different lines synchronously arrive at transfer stations. Due to the well-designed coordination of bus timetables, passengers can make a smooth transfer without waiting a long time for connecting buses. This paper addresses the planning level of resynchronizing of bus timetable problem allowing modifications to initial timetable. Timetable modifications consist of shifts in the departure times and headways. A single-objective mixed-integer programming model is proposed for this problem to maximize the number of total transferring passengers benefiting from smooth transfers. We analyze the mathematical properties of this model, and then a preprocessing method is designed to reduce the solution space of the proposed model. The numerical results show that the reduced model is effectively solved by branch and bound algorithm, and the preprocessing method has the potential to be applied for large-scale bus networks.
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2

Takamatsu, Mizuyo, and Azuma Taguchi. "Bus Timetable Design to Ensure Smooth Transfers in Areas with Low-Frequency Public Transportation Services." Transportation Science 54, no. 5 (September 2020): 1238–50. http://dx.doi.org/10.1287/trsc.2019.0918.

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Анотація:
This study investigates the timetable design problem in areas with low-frequency public transportation services. In Japan, rural areas face sparse populations and rapid growth in the percentage of elderly people. In these areas, many bus lines offer fewer than 10 services per day. In addition to low-frequency services, it is also inconvenient to transfer to another bus or train service. Thus, there is a strong need to design a timetable that ensures smooth transfers among buses and trains. We tackle this problem by adopting existing bus lines and train timetables as much as possible to avoid drastic changes such as an increase in the number of services. Based on this approach, we present a mathematical optimization model to generate a revised bus timetable that shortens waiting time for transfers compared with the current timetable. We apply our model to a part of the Tohoku District in Japan and demonstrate its usefulness in the real world.
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3

Peng, Yong, Zhiyao Mo, and Song Liu. "Passenger’s routes planning in stochastic common-lines’ multi-modal transportation network through integrating Genetic Algorithm and Monte Carlo simulation." Archives of Transport 59, no. 3 (September 30, 2021): 73–92. http://dx.doi.org/10.5604/01.3001.0015.0123.

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Анотація:
In the urban transportation network, most passengers choose public transportation to travel. However, bad weather, accidents, traffic jams and other factors lead to uncertainty in transportation network. Besides, transport vehicles running on the same segments of routes and belonging to different modes or routes make the transportation network more complicated. In order to improve the efficiency of passenger’s travel, this paper aim to introducing an approach for optimizing passenger travel routes. This approach takes the travel cost and the number of transfers as constraints to finding the shortest total travel duration of passenger in urban transporta-tion network. The running duration and dwell duration of the vehicles in the network are uncertain, and the vehicles are running according to the timetables. As transportation modes, bus, rail transit and walk are consid-ered. In terms of methodological contribution, this paper combines Genetic Algorithm (GA) and Monte Carlo simulation to deal with optimization problem under stochastic conditions. This paper uses Monte Carlo simula-tion to simulate the running duration and dwell time of vehicles in different scenarios to deal with the uncertainty of the network. The shortest path of passenger’s travel is solved by GA. Two kinds of population management strategies including single population management strategy and multiple population management strategy are designed to guide the solution population evolving process. The two kinds of population management strategies of GA are tested in numerical example. The satisfactory convergence performance and efficiency of the model and algorithm is verified by the numerical example. The numerical example also demonstrated that the multiple population management strategy of GA can get better results in a shorter CPU time. At the same time, the influ-ences of some significant variables on solution are performed. This paper is able to provide a scientific quantita-tive support to the path scheme selection under the influence of common-lines and timetables of different modes of transportation in stochastic urban multimodal transportation network.
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4

Boyd, Brent, Melissa Chow, Robert Johnson, and Alexander Smith. "Analysis of Effects of Fare-Free Transit Program on Student Commuting Mode Shares: BruinGo at University of California at Los Angeles." Transportation Research Record: Journal of the Transportation Research Board 1835, no. 1 (January 2003): 101–10. http://dx.doi.org/10.3141/1835-13.

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Анотація:
Spring 2002 concluded the second year of the BruinGo pilot demonstration program of the University of California at Los Angeles (UCLA). BruinGo allows students and employees of UCLA to board buses of the Santa Monica Municipal Bus Lines (Big Blue Bus) free of charge. At a time when the future of BruinGo is at stake (both its existence and the possible expansion of the program to other transit agencies), a brief analys is of what has been accomplished by the program at this stage is provided. The program is analyzed using two methods: ( a) the analysis of the changes in the commuting mode share for all off-campus student commuters and ( b) an intricate process of geocoding survey data in which the relationship of the proximity of a student’s residence to the Big Blue Bus lines and the corresponding choice of mode to campus is analyzed. The conclusion is that providing fare-free transit to students did, in fact, increase transit ridership and decrease students’ reliance on the automobile to reach campus. Transit ridership for 2001 (the first year of BruinGo) increased by more than 50% over ridership in 2000 (the year before BruinGo), while more than 1,000 fewer automobile trips were taken to the UCLA campus each day. Even more striking is the rate at which students are leaving their cars at home in the areas best served by the Big Blue Bus. After BruinGo, fully 50% of all students in walking distance of a direct line to campus took transit (compared with 35% before BruinGo). That is much higher than in other areas. The mode share of walking and bicycling also decreased dramatically, however.
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5

Parshina, Valentina, and Elena Kuznetsova. "Interaction between industry higher educational institutions and the customer of educational services." E3S Web of Conferences 135 (2019): 04001. http://dx.doi.org/10.1051/e3sconf/201913504001.

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Анотація:
The purpose of the article is to develop a model for interaction between industry higher educational institutions and the customer of educational services in order to increase the human potential in the industry. The article deals with the specifics of relations between the transport higher educational institutions and the company. To assess the quality of relations, the resource exchange model is suggested for use. The article formulates principles of interaction between the parties and indicators that can be used to assess the quality of the resources exchange. A model for interaction between the company’s bus iness units and higher educational institutions was proposed. The relations between the horizontal-structured corporation and educational institutions were modeled; the mathematical apparatus was selected to describe the contacts, indicators of satisfaction with the resources and the resultant indicator (satisfaction with the interaction) were proposed. The model will help to determine quantitative characteristics of the achieved contacts. Their introduction will make it possible to assess the original state of the contacts and proceed to functional design. Introduction of the concept of satisfaction with the resources and interaction in its individual lines will allow identifying the reserves to build on in order to optimize the contacts. The purpose of the modeling is to expand contacts between the higher educational institution and enterprises in the industry, to involve employees in innovation activities, to improve skills of the higher educational institution graduates in response to the needs of the industry. This article only looks at the interaction between industry higher educational institutions and business units of RZD OJSC, whereas recent years brought contacts between the university and many transport organizations that have specifics of market interactions described in the stakeholder theory.
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6

Xinchao, Zhao, Sun Hao, Lu Juan, and Li Zhiyu. "DP-TABU: an algorithm to solve single-depot multi-line vehicle scheduling problem." Complex & Intelligent Systems, June 19, 2021. http://dx.doi.org/10.1007/s40747-021-00443-5.

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Анотація:
AbstractA DP-TABU algorithm is proposed which can effectively solve the multi-line scheduling problem of single Deport (SD-ML-VSP). The multi-line regional coordinated dispatch of the single-line deport of the bus is to solve the problems of idle low-peak vehicles and insufficient peak capacity in single-line scheduling. The capacity of multiple lines at the same station is adjusted to realize resource sharing such as timetables, vehicles, and drivers. Shared capacity such as bus departure intervals and bus schedules. Taking the regional scheduling of multiple lines at the same station as the service object, a vehicle operation planning model based on the objective of optimal public transportation resources (minimum bus and driver costs) is established to optimize the vehicle dispatching mode of multiple lines. We applied this algorithm to the three lines S105, S107, and S159 of Zhengzhou Public Transport Corporation, and the results proved that the algorithm is effective. Through comparison with manual scheduling and simulated annealing algorithm, the advantages of DP-TABU algorithm in performance optimization and robustness are further verified.
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Дисертації з теми "Bus lines Employees Timetables"

1

Chan, Su-yee, and 曾淑儀. "The value of real time information at bus stop in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B3194565X.

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2

Berrebi, Simon Jonas Youna. "A real-time bus dispatching policy to minimize headway variance." Thesis, Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51899.

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Анотація:
Transit agencies include buffer time in their schedules to maintain stable headways and avoid bus bunching. In this work, a real-time holding mechanism is proposed to dispatch buses on a loop-shaped route, solely based on operating conditions in real-time. Holds are applied at the terminal station to minimize the expected variance of bus headways at departure. The bus-dispatching problem is formulated as a stochastic decision process. The optimality equations are derived and structural properties of the optimal policy are inferred by backward induction. The exact optimal holding policy is then found in closed form, as a function of the expected travel time of buses currently running. A simulation assuming stochastic operating conditions and unstable headway dynamics is performed to assess the expected average waiting time of passengers at stations. The proposed control strategy is found to provide lower passenger waiting time and better resiliency than methods recommended in the literature and used in practice.
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Книги з теми "Bus lines Employees Timetables"

1

Doe, Barry S. Doe's directory of bus timetables & enquiry offices. 2nd ed. Bournemouth (25 Newmorton Rd., Moordown, Bournemouth, Dorset BH9 3NU): Barry S. Doe, 1997.

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2

Manabe, Ryutarō. Scheduling buses by the network flow model on the personal computer. Tarumi, Kobe, Japan: Institute of Economic Research, Kobe University of Commerce, 1986.

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3

Berryhill, Robert. Bus across Mexico: A unique guide for the young at heart. Oakland, CA: Bengi Pub., 2001.

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4

New York (State). Metropolitan Transportation Authority. Office of the Inspector General. An examination of the impact of revisions to certain New York City Transit Authority bus schedules. [New York, N.Y.]: Office of the Inspector General, Metropolitan Transportation Authority, 1987.

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5

Aravindekara, Santosha. Mājhī kaṇḍakṭarī. Puṇe: Anubandha Prakāśana, 2012.

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6

Womar, J. W. Turning points: A lifetimein transport. Glossop: Venture, 1995.

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7

Olaoba, O. B. Business on the wheels: Bus conducting and social conflicts in Ibadan city. [Nigeria]: Rex Charles Publication in association with Connel Publication, 2002.

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8

R, Blackburn Diane, Transit Cooperative Research Program, National Research Council (U.S.). Transportation Research Board., United States. Federal Transit Administration., and Transit Development Corporation, eds. Changing roles and practices of bus field supervisors. Washington, D.C: National Academy Press, 1996.

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9

The forgotten workers: The case of public service vehicle drivers in Eldoret Town, Kenya. Addis Ababa, Ethiopia: Organization for Social Science Research in Eastern and Southern Africa, 2001.

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10

United States. Congress. House. Committee on Transportation and Infrastructure. Subcommittee on Oversight, Investigations, and Emergency Management. Federal agency shuttles: Hearing before the Subcommittee on Oversight, Investigations, and Emergency Management of the Committee on Transportation and Infrastructure, House of Representatives, One Hundred Sixth Congress, second session, September 13, 2000. Washington: U.S. G.P.O., 2001.

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Частини книг з теми "Bus lines Employees Timetables"

1

Naumov, Vitalii. "Synchronisation of Timetables for Public Bus Lines Using Genetic Algorithms and Computer Simulations." In Lecture Notes in Networks and Systems, 44–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74454-4_4.

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Тези доповідей конференцій з теми "Bus lines Employees Timetables"

1

Tušek, Ivana, and Miha Marič. "Izzivi pri odločanju glede načina prevoza na delo." In Values, Competencies and Changes in Organizations. University of Maribor Press, 2021. http://dx.doi.org/10.18690/978-961-286-442-2.69.

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Анотація:
Public transport in Slovenia is poorly organized. The connections and timetables are poor, trains are not as fast, and the savings are not significant if the transportation of choice is a personal automobile. However, this mode of transportation more often than not involves a parking problem. Every company does not have enough parking spaces for all of their employees, which is why some people opt to drive to work together or start from home early to secure a free parking space. We will prepare an overview of the possibilities of transport to work in Slovenia, focusing on the route Ljubljana - Kranj. We will address the issues discussed from the point of view of the mode of transport to work - car, train, bus or even on foot, if the workplace is close to home. Our purpose is to determine whether we would save time and money if we were to travel to work by another means of transport, and to identify other factors that influence our decision regarding the mode of transport to work.
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