Balanced maximal covering location problem and its application in bike-sharing

Muren,, Hao Li, Samar K. Mukhopadhyay, Jian-jun Wu, Li Zhou and Zhiping Du

International Journal of Production Economics, 2020, vol. 223, issue C

Abstract: With the rapid growth of large-scale cities and the reinforcement of environmental concepts and sustainability, the sharing economy has received increasing attention. The maximum coverage location problem (MCLP), which is the basis of many sharing economy models, aims to cover more customers with a specified number of centers and radii. Many scholars have studied the MCLP Model from various angles and have achieved workload balance under maximum coverage by setting the upper limit of each center's workload. However, there has been little research involving the lower limit of the center. We propose a new MCLP model that includes a lower bound that would improve the quality of results. We also introduce the concept of “balance” that will reduce the imbalance of service levels at various locations. We call the proposed model balanced maximum coverage location problem (BMCLP). We test our model on the bike-sharing problem in a large Chinese city. Our results show the twin accomplishments of better maximal covering results and balanced service. We also show that our model is general enough to be applied to many sharing economy problems.

Keywords: MCLP; Mixed integer programming; Iteration; Sharing economy; Bike-sharing (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:223:y:2020:i:c:s0925527319303342

DOI: 10.1016/j.ijpe.2019.09.034

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