Using metaheuristics for the location of bicycle stations. (15th December 2020)

• Record Type: Journal Article
• Authors: Cintrano, C.; Chicano, F.; Alba, E.
• Is Part Of: Expert systems with applications. Volume 161(2020)
• Publication Date: 2020-12-15
• Subjects: Bike station location -- p-Median problem -- Metaheuristics; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.113684
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: We considered not only real data: population, geographic, and use. We have used five different metaheuristic algorithms: GA, ILS, PSO, SA, and VNS. We have configured all these algorithms automatically using irace. We analyze the algorithm performances and the best model approach. We can improve the current system of Malaga by adding more stations. Abstract: 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.