TITLE:
Route Search Method for Railway Replacement Buses Adopting Ant Colony Optimization
AUTHORS:
Kei Nagaoka, Kayoko Yamamoto
KEYWORDS:
Local Railway Line, Railway Replacement Bus, Route Search Method, Ant Colony Optimization (ACO), Dijkstra’s Algorithm, Geographic Information Systems (GIS)
JOURNAL NAME:
Journal of Geographic Information System,
Vol.15 No.4,
August
16,
2023
ABSTRACT: In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.