Optimizing Customized Transit Service considering Stochastic Bus Arrival Time
The introduction of customized bus (CB) service intends to expand and elevate existing transit service, which offers an efficient and sustainable alternative to serve commuters. A probabilistic model is proposed to optimize CB service with mixed vehicle sizes in an urban setting considering stochast...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/3207025 |
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| _version_ | 1832545967078899712 |
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| author | Qian Sun Steven Chien Dawei Hu Xiqiong Chen |
| author_facet | Qian Sun Steven Chien Dawei Hu Xiqiong Chen |
| author_sort | Qian Sun |
| collection | DOAJ |
| description | The introduction of customized bus (CB) service intends to expand and elevate existing transit service, which offers an efficient and sustainable alternative to serve commuters. A probabilistic model is proposed to optimize CB service with mixed vehicle sizes in an urban setting considering stochastic bus arrival time and spatiotemporal demand, which minimizes total cost subject to bus capacity and time window constraints. The studied optimization problem is combinatorial with many decision variables including vehicle assignment, bus routes, timetables, and fleet size. A heuristic algorithm is developed, which integrates a hybrid genetic algorithm (HGA) and adaptive destroy-and-repair (ADAR) method. The efficiency of HGA-ADAR is demonstrated through numerical comparisons to the solutions obtained by LINGO and HGA. Numerical instances are carried out, and the results suggested that the probabilistic model considering stochastic bus arrival time is valuable and can dramatically reduce the total cost and early and late arrival penalties. A case study is conducted in which the proposed model is applied to optimize a real-world CB service in Xi’an, China. The relationship between decision variables and model parameters is explored. The impacts of time window and variance of bus arrival time, which significantly affect service reliability, are analysed. |
| format | Article |
| id | doaj-art-05e447866e0b4ccb8bc936d6cc23a68d |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-05e447866e0b4ccb8bc936d6cc23a68d2025-02-03T07:24:13ZengWileyJournal of Advanced Transportation2042-31952021-01-01202110.1155/2021/3207025Optimizing Customized Transit Service considering Stochastic Bus Arrival TimeQian Sun0Steven Chien1Dawei Hu2Xiqiong Chen3School of Transportation EngineeringSchool of Transportation EngineeringSchool of Transportation EngineeringSchool of Transportation EngineeringThe introduction of customized bus (CB) service intends to expand and elevate existing transit service, which offers an efficient and sustainable alternative to serve commuters. A probabilistic model is proposed to optimize CB service with mixed vehicle sizes in an urban setting considering stochastic bus arrival time and spatiotemporal demand, which minimizes total cost subject to bus capacity and time window constraints. The studied optimization problem is combinatorial with many decision variables including vehicle assignment, bus routes, timetables, and fleet size. A heuristic algorithm is developed, which integrates a hybrid genetic algorithm (HGA) and adaptive destroy-and-repair (ADAR) method. The efficiency of HGA-ADAR is demonstrated through numerical comparisons to the solutions obtained by LINGO and HGA. Numerical instances are carried out, and the results suggested that the probabilistic model considering stochastic bus arrival time is valuable and can dramatically reduce the total cost and early and late arrival penalties. A case study is conducted in which the proposed model is applied to optimize a real-world CB service in Xi’an, China. The relationship between decision variables and model parameters is explored. The impacts of time window and variance of bus arrival time, which significantly affect service reliability, are analysed.http://dx.doi.org/10.1155/2021/3207025 |
| spellingShingle | Qian Sun Steven Chien Dawei Hu Xiqiong Chen Optimizing Customized Transit Service considering Stochastic Bus Arrival Time Journal of Advanced Transportation |
| title | Optimizing Customized Transit Service considering Stochastic Bus Arrival Time |
| title_full | Optimizing Customized Transit Service considering Stochastic Bus Arrival Time |
| title_fullStr | Optimizing Customized Transit Service considering Stochastic Bus Arrival Time |
| title_full_unstemmed | Optimizing Customized Transit Service considering Stochastic Bus Arrival Time |
| title_short | Optimizing Customized Transit Service considering Stochastic Bus Arrival Time |
| title_sort | optimizing customized transit service considering stochastic bus arrival time |
| url | http://dx.doi.org/10.1155/2021/3207025 |
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