2016
DOI: 10.1002/atr.1400
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Fixed‐route taxi system: route network design and fleet size minimization problems

Abstract: Summary This paper introduces the taxi route network design problem (TXRNDP) for a fixed‐route taxi service operating in Iran and, in similar form, in various other developing countries. The service operates fairly similar to regular transit services in that vehicles are only permitted to follow a certain predetermined route on the network. The service is provided with small size vehicles and main features are that vehicles only depart if full and that there are no intermediate boarding stops. In Iran the serv… Show more

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Cited by 10 publications
(4 citation statements)
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References 58 publications
(76 reference statements)
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“…Among the causes are the characteristics of the DFS algorithm. Other studies on ride-sharing and fixed-route taxi algorithms also experience performance problems and require an optimization in algorithm performances [16] [17]. An adaptation or modification of dynamic programming (DP) algorithm can be used to improve the performance of the trip planning algorithm [18].…”
Section: Discussionmentioning
confidence: 99%
“…Among the causes are the characteristics of the DFS algorithm. Other studies on ride-sharing and fixed-route taxi algorithms also experience performance problems and require an optimization in algorithm performances [16] [17]. An adaptation or modification of dynamic programming (DP) algorithm can be used to improve the performance of the trip planning algorithm [18].…”
Section: Discussionmentioning
confidence: 99%
“…Similarly, Babaei et al. (2016) propose a framework to plan fixed‐route taxi services with an application in Iran. Li et al.…”
Section: Application Areasmentioning
confidence: 99%
“…Zhaowei Qu [6] and others based on the taxi GPS data and combined the TSLM model to study the impact of the passenger's maximum acceptable distance on the TSLP. Babaei et al [7] studied the case of Zanjan city in Iran and established a linear scale to obtain a function to reduce total travel time, total waiting time and taxi route optimization. Kim [8] et al studied the airport gates and used algorithms such as tabu search to solve the problem of taxi congestion on the airport ramp, resulting in delayed boarding, and made the circulation on the passenger terminal and ramp effective.…”
Section: Introductionmentioning
confidence: 99%
“…However, most of the existing literature only solved the problem of airport route planning [11,12] or the forecast of taxi numbers [13] , and few studies have been conducted on the number of taxis released in each batch and the specific locations of the boarding locations. Therefore, this paper first established a multi-objective programming model based on reducing the conflict between people and vehicles, and maximizing efficiency and comfort.…”
Section: Introductionmentioning
confidence: 99%