scholarly journals Fleet size and fare optimization for taxi under dynamic demand

2016 ◽  
Vol 10 (4) ◽  
pp. 45-50 ◽  
Author(s):  
Baozhen Yao ◽  
Lu Jin ◽  
Qingda Cao ◽  
Junjie Gao ◽  
Mingheng Zhang
Keyword(s):  
2008 ◽  
Author(s):  
Jennifer Leigh Kohn ◽  
Robert H. Patrick
Keyword(s):  

Procedia CIRP ◽  
2021 ◽  
Vol 96 ◽  
pp. 260-265
Author(s):  
Ahmet Yükseltürk ◽  
Aleksandra Wewer ◽  
Pinar Bilge ◽  
Franz Dietrich

Author(s):  
Hu Zhao ◽  
Shumin Feng ◽  
Yusheng Ci

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.


Author(s):  
Andrii Galkin ◽  
Tkachenko Iryna ◽  
Vladyka Yulia ◽  
Natalya Shyllye ◽  
Oksana Hulchak ◽  
...  
Keyword(s):  

2019 ◽  
Vol 151 ◽  
pp. 878-883 ◽  
Author(s):  
Golan Ben-Dor ◽  
Eran Ben-Elia ◽  
Itzhak Benenson

2020 ◽  
Vol 12 (11) ◽  
pp. 4563
Author(s):  
Sangpil Ko ◽  
Pasi Lautala ◽  
Kuilin Zhang

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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