A branch and price approach for routing and refueling station location model

•We study the refueling station location problem with routing considerations.•We propose a branch and price algorithm based on the notion of path-segments.•The decrease in solution times with respect to existing works is significant.•Our algorithm scales very efficiently to more realistic network di...

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Bibliographic Details
Published in:European journal of operational research Vol. 248; no. 3; pp. 815 - 826
Main Authors: Yıldız, Barış, Arslan, Okan, Karaşan, Oya Ekin
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.02.2016
Elsevier Sequoia S.A
Subjects:
Alternative fuel vehicles
Branch and price
Combinatorial optimization
Location
Location analysis
Network flow problem
Refueling station
Route optimization
Shortest path algorithms
Studies
Transportation problem (Operations research)
Branch and price
Combinatorial optimization
Alternative fuel vehicles
Refueling station
Location
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:•We study the refueling station location problem with routing considerations.•We propose a branch and price algorithm based on the notion of path-segments.•The decrease in solution times with respect to existing works is significant.•Our algorithm scales very efficiently to more realistic network dimensions. The deviation flow refueling location problem is to locate p refueling stations in order to maximize the flow volume that can be refueled respecting the range limitations of the alternative fuel vehicles and the shortest path deviation tolerances of the drivers. We first provide an enhanced compact model based on a combination of existing models in the literature for this relatively new operations research problem. We then extend this problem and introduce the refueling station location problem which adds the routing aspect of the individual drivers. Our proposed branch and price algorithm relaxes the simple path assumption generally adopted in the existing studies and implicitly takes into account deviation tolerances without the pregeneration of the routes. Therefore, the decrease in solution times with respect to existing models is significant and our algorithm scales very efficiently to more realistic network dimensions.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2015.05.021