A Hybrid Genetic Algorithm for Solving the VRP with Pickup and Delivery in Rural Areas

dc.contributor.author Stadler, Timo
dc.contributor.author Schrader, Jonas
dc.contributor.author Dünnweber, Jan
dc.date.accessioned 2022-12-27T19:16:57Z
dc.date.available 2022-12-27T19:16:57Z
dc.date.issued 2023-01-03
dc.description.abstract In this paper, we present a new Hybrid Genetic Search (HGS) algorithm for solving the Capacitated Vehicle Routing Problem for Pickup and Delivery (CVRPPD) as it is required for public transport in rural areas. One of the biggest peculiarities here is that a large area has to be covered with as few vehicles as possible. The basic idea of this algorithm is based on a more general version of HGS, which we adopted to solve the CVRPPD in rural areas. It also implements improvements that lead to the acceleration of the algorithm and, thereby, to a faster generation of a fastest route. For example, we use a modified form of the 2Opt method. We tested the algorithm on real road data from Roding, a rural district in Bavaria, Germany. Moreover, we designed an API for converting data from the Openrouteservice, so that our algorithm can be applied on real world examples as well.
dc.format.extent 9
dc.identifier.doi 10.24251/HICSS.2023.617
dc.identifier.isbn 978-0-9981331-6-4
dc.identifier.uri https://hdl.handle.net/10125/103251
dc.language.iso eng
dc.relation.ispartof Proceedings of the 56th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject GIS, Industry 4.0, and Sustainability
dc.subject genetic algorithm
dc.subject pickup and delivery
dc.subject vrp
dc.title A Hybrid Genetic Algorithm for Solving the VRP with Pickup and Delivery in Rural Areas
dc.type.dcmi text
prism.startingpage 5039
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