TY - JOUR
T1 - Railway flow interception location model
T2 - Model development and case study of Tokyo metropolitan railway network
AU - Tanaka, Ken ichi
AU - Furuta, Takehiro
AU - Toriumi, Shigeki
N1 - Funding Information:
The authors are grateful for the three anonymous reviewers for their careful reading of the original version of our manuscript and for providing valuable and insightful suggestions. This work was supported by JSPS KAKENHI Grant Number 18H01661 and 18H01662 .
Publisher Copyright:
© 2018 The Authors
PY - 2019
Y1 - 2019
N2 - The flow interception location model (FILM) focuses on vehicular traffic in a road network and locates a fixed number of facilities so as to maximize the total flow that can be serviced at facilities along preplanned routes, such as a daily commute to work. This paper develops a version of FILM, the railway flow interception location model (R-FILM), that explicitly focuses on railway passenger flows. For railway users, accessing a facility placed at an origin, destination, or transfer station (ODT station) is easier than visiting a facility at other stations included in the travel path. Accessing a facility at a non-ODT station involves the additional cost of disembarking the train to obtain a service and then boarding another train after consuming the service. R-FILM introduces this railway-specific structure to FILM by introducing two different coverages according to the types of station intercepted for each flow. Concretely, a given flow is called strongly covered when at least one facility is located at an ODT station. Similarly, a given flow is called weakly covered when no facility is located at an ODT station, but at least one facility is located among stations included in the travel path. We present an integer programming formulation of the proposed R-FILM. Using it, we conduct a large-scale case study of the Tokyo metropolitan railway network, which includes about 1500 railway stations. Input flow is constructed using census data for commuter traffic, with about 100,000 distinct flow paths. Optimal solutions of both models for single- and multi-facility problems are analyzed. In R-FILM solutions, large terminal stations tend to be selected more often than with FILM.
AB - The flow interception location model (FILM) focuses on vehicular traffic in a road network and locates a fixed number of facilities so as to maximize the total flow that can be serviced at facilities along preplanned routes, such as a daily commute to work. This paper develops a version of FILM, the railway flow interception location model (R-FILM), that explicitly focuses on railway passenger flows. For railway users, accessing a facility placed at an origin, destination, or transfer station (ODT station) is easier than visiting a facility at other stations included in the travel path. Accessing a facility at a non-ODT station involves the additional cost of disembarking the train to obtain a service and then boarding another train after consuming the service. R-FILM introduces this railway-specific structure to FILM by introducing two different coverages according to the types of station intercepted for each flow. Concretely, a given flow is called strongly covered when at least one facility is located at an ODT station. Similarly, a given flow is called weakly covered when no facility is located at an ODT station, but at least one facility is located among stations included in the travel path. We present an integer programming formulation of the proposed R-FILM. Using it, we conduct a large-scale case study of the Tokyo metropolitan railway network, which includes about 1500 railway stations. Input flow is constructed using census data for commuter traffic, with about 100,000 distinct flow paths. Optimal solutions of both models for single- and multi-facility problems are analyzed. In R-FILM solutions, large terminal stations tend to be selected more often than with FILM.
KW - Discrete location problem
KW - Flow interception location model
KW - Integer programming
KW - Railway passenger flow
KW - Tokyo metropolitan railway network
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U2 - 10.1016/j.orp.2018.11.001
DO - 10.1016/j.orp.2018.11.001
M3 - Article
AN - SCOPUS:85058812357
SN - 2214-7160
VL - 6
JO - Operations Research Perspectives
JF - Operations Research Perspectives
M1 - 100085
ER -