Study on the minimum fleet size based on deadheading time threshold

Sudden passenger demand at a bus stop can lead to numerous passengers gathering at the stop, which can affect bus system operation. Bus system operators often deal with this problem by adopting peer-to-peer service, where empty buses are added to the fleet and dispatched directly to the stop where passengers are gathered (PG-stop). However, with this strategy, passengers at the PG-stop have a long waiting time to board a bus. Thus, this paper proposes a novel mathematical programming model to reduce the passenger waiting time at a bus stop. A more complete stop-skipping model that including four cases for passengers’ waiting time at bus stops is proposed in this study. The stop-skipping decision and fleet size are modeled as a dynamic program to obtain the optimal strategy that minimizes the passenger waiting time, and the optimization model is solved with an improved ant colony algorithm. The proposed strategy was implemented on a bus line in Harbin, China. The results show that, during the evacuation, using the stop-skipping strategy not only reduced the total waiting time for passengers but also decreased the proportion of passengers with a long waiting time (>6 min) at the stops. Compared with the habitual and peer-to-peer service strategies, the total waiting time for passengers is reduced by 31% and 23%, respectively. Additionally, the proportion of passengers with longer waiting time dropped to 43.19% by adopting the stop-skipping strategy, compared with 72.68% with the habitual strategy and 47.5% with the peer-to-peer service strategy.

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Potential Economic Benefits and Optimum Fleet Size in the Pacific Coast Trawl Fleet

Marine Resource Economics ◽

10.1086/mre.3.4.42628967 ◽

1986 ◽

Vol 3 (4) ◽

pp. 297-318 ◽

Cited By ~ 2

Author(s):

Daniel D. Huppert ◽

Dale Squires

Keyword(s):

Pacific Coast ◽

Economic Benefits ◽

Fleet Size ◽

The Pacific

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Fleet size problem for Secure Food Chain with a certain range of transportation temperature

2020 13th International Conference on Developments in eSystems Engineering (DeSE) ◽

10.1109/dese51703.2020.9450786 ◽

2020 ◽

Author(s):

Andrii Galkin ◽

Tkachenko Iryna ◽

Vladyka Yulia ◽

Natalya Shyllye ◽

Oksana Hulchak ◽

...

Keyword(s):

Food Chain ◽

Fleet Size ◽

Size Problem

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Introducing fairness in Norwegian air ambulance base location planning

Scandinavian Journal of Trauma Resuscitation and Emergency Medicine ◽

10.1186/s13049-021-00842-0 ◽

2021 ◽

Vol 29 (1) ◽

Author(s):

Caroline J. Jagtenberg ◽

Maaike A. J. Vollebergh ◽

Oddvar Uleberg ◽

Jo Røislien

Keyword(s):

Social Welfare ◽

Social Welfare Function ◽

Mathematical Optimization ◽

Population Coverage ◽

Air Ambulance ◽

Service Levels ◽

Remote Areas ◽

The North ◽

Time Threshold ◽

Essential Question

Abstract Background A primary task of the Norwegian helicopter emergency medical services (HEMS) is to provide advanced medical care to the critical ill and injured outside of hospitals. Where HEMS bases are located, directly influences who in the population can be reached within a given response time threshold and who cannot. When studying the locations of bases, the focus is often on efficiency, that is, maximizing the total number of people that can be reached within a given set time. This approach is known to benefit people living in densely populated areas, such as cities, over people living in remote areas. The most efficient solution is thus typically not necessarily a fair one. This study aims to incorporate fairness in finding optimal air ambulance base locations. Methods We solve multiple advanced mathematical optimization models to determine optimal helicopter base locations, with different optimization criteria related to the level of aversion to inequality, including the utilitarian, Bernoulli-Nash and iso-elastic social welfare functions. This is the first study to use the latter social welfare function for HEMS. Results Focusing on efficiency, a utilitarian objective function focuses on covering the larger cities in Norway, leaving parts of Norway largely uncovered. Including fairness by rather using an iso-elastic social welfare function in the optimization avoids leaving whole areas uncovered and in particular increases service levels in the north of Norway. Conclusions Including fairness in determining optimal HEMS base locations has great impact on population coverage, in particular when the number of base locations is not enough to give full coverage of the country. As results differ depending on the mathematical objective, the work shows the importance of not only looking for optimal solutions, but also raising the essential question of ‘optimal with respect to what’.

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Dynamic Scheduling Algorithm in Cyber Mimic Defense Architecture of Volunteer Computing

ACM Transactions on Internet Technology ◽

10.1145/3408291 ◽

2021 ◽

Vol 21 (3) ◽

pp. 1-33

Author(s):

Qianmu Li ◽

Shunmei Meng ◽

Xiaonan Sang ◽

Hanrui Zhang ◽

Shoujin Wang ◽

...

Keyword(s):

Dynamic Scheduling ◽

Scheduling Algorithm ◽

Dynamic Change ◽

High Energy ◽

Transformation Rule ◽

Volunteer Computing ◽

Attack Behavior ◽

Time Threshold ◽

Security And Reliability ◽

Multi Level

Volunteer computing uses computers volunteered by the general public to do distributed scientific computing. Volunteer computing is being used in high-energy physics, molecular biology, medicine, astrophysics, climate study, and other areas. These projects have attained unprecedented computing power. However, with the development of information technology, the traditional defense system cannot deal with the unknown security problems of volunteer computing . At the same time, Cyber Mimic Defense (CMD) can defend the unknown attack behavior through its three characteristics: dynamic, heterogeneous, and redundant. As an important part of the CMD, the dynamic scheduling algorithm realizes the dynamic change of the service centralized executor, which can enusre the security and reliability of CMD of volunteer computing . Aiming at the problems of passive scheduling and large scheduling granularity existing in the existing scheduling algorithms, this article first proposes a scheduling algorithm based on time threshold and task threshold and realizes the dynamic randomness of mimic defense from two different dimensions; finally, combining time threshold and random threshold, a dynamic scheduling algorithm based on multi-level queue is proposed. The experiment shows that the dynamic scheduling algorithm based on multi-level queue can take both security and reliability into account, has better dynamic heterogeneous redundancy characteristics, and can effectively prevent the transformation rule of heterogeneous executors from being mastered by attackers.

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Determining an Optimal Fleet Size for a Reliable Shared Automated Vehicle Ride-Sharing Service

Procedia Computer Science ◽

10.1016/j.procs.2019.04.121 ◽

2019 ◽

Vol 151 ◽

pp. 878-883 ◽

Cited By ~ 3

Author(s):

Golan Ben-Dor ◽

Eran Ben-Elia ◽

Itzhak Benenson

Keyword(s):

Fleet Size ◽

Automated Vehicle ◽

Ride Sharing

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Data-Driven Study on the Sustainable Log Movements: Impact of Rail Car Fleet Size on Freight Storage and Car Idling

Sustainability ◽

10.3390/su12114563 ◽

2020 ◽

Vol 12 (11) ◽

pp. 4563

Author(s):

Sangpil Ko ◽

Pasi Lautala ◽

Kuilin Zhang

Keyword(s):

Service Life ◽

Seasonal Dynamics ◽

Lake Superior ◽

Data Driven ◽

Short Term ◽

Fleet Size ◽

Interesting Observation ◽

The Us ◽

Term Storage ◽

Scale Data

Rail car availability and the challenges associated with the seasonal dynamics of log movements have received growing attentions in the Lake Superior region of the US, as a portion of rail car fleet is close to reaching the end of its service life. This paper proposes a data-driven study on the rail car peaking issue to explore the fleet of rail cars dedicated to being used for log movements in the region, and to evaluate how the number of cars affects both the storage need at the sidings and the time the cars are idled. This study is based on the actual log scale data collected from a group of forest companies in cooperation with the Lake State Shippers Association (LSSA). The results of our analysis revealed that moving the current log volumes in the region would require approximately 400–600 dedicated and shared log cars in ideal conditions, depending on the specific month. While the higher fleet size could move the logs as they arrive to the siding, the lower end would nearly eliminate the idling of rail cars and enable stable volumes throughout the year. However, this would require short-term storage and additional handling of logs at the siding, both elements that increase the costs for shippers. Another interesting observation was the fact that the reduction of a single day in the loading/unloading process (2.5 to 1.5 days) would eliminate almost 100 cars (20%) of the fleet without reduction in throughput.

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