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

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. In fact, for shared economic models, guaranteed services and balanced services are crucial for companies. Therefore, according to the basic theory of multiobjective optimization, a balanced maximal covering location problem (BMCLP) is proposed to determine a better design for maximal covering and balanced workload. Using the BMCLP Model successfully in a bike-sharing problem demonstrates that it is more general than the MCLP with demonstrated bounds.