RT Journal Article
T1 Using metaheuristics for the location of bicycle stations
A1 Cintrano López, Christian
A1 Chicano-García, José-Francisco
A1 Alba-Torres, Enrique
K1 Optimización matemática
AB In this work, we solve the problem of finding the best locations to place stations for depositing/collecting shared bicycles. To do this, we model the problem as the p-median problem, that is a major existing localization problem in optimization. The p-median problem seeks to place a set of facilities (bicycle stations) in a way that minimizes the distance between a set of clients (citizens) and their closest facility (bike station).  We have used a genetic algorithm, iterated local search, particle swarm optimization, simulated annealing, and variable neighbourhood search, to find the best locations for the bicycle stations and study their comparative advantages. We use irace to parameterize each algorithm automatically, to contribute with a methodology to fine-tune algorithms automatically. We have also studied different real data (distance and weights) from diverse open data sources from a real city, Malaga (Spain), hopefully leading to a final smart city application. We have compared our results with the implemented solution in Malaga. Finally, we have analyzed how we can use our proposal to improve the existing system in the city by adding more stations.
PB Elsevier
YR 2020
FD 2020
LK https://hdl.handle.net/10630/29774
UL https://hdl.handle.net/10630/29774
LA eng
NO Christian Cintrano, Francisco Chicano, Enrique Alba: Using metaheuristics for the location of bicycle stations. Expert Syst. Appl. 161: 113684 (2020)
NO This research was partially funded by the University of Málaga, Andalucía Tech, the Spanish MINECO and FEDER projects: TIN2014-57341-R, TIN2016-81766-REDT, and TIN2017-88213-R.C. Cintrano is supported by a FPI grant (BES-2015-074805) from Spanish MINECO.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 1 mar 2026