Utilizing node importance to maximize locations coverage in a bike share system network

In this paper, we propose an optimization method that uses node importance to maximize locations coverage in a Bike Share System (BSS). The method implements the Maximal Covering Location Problem (MCLP) to maximize the BSS demand coverage within a service distance. Node importance is defined based on how close the solution is to the positive ideal solution which has the best performance values of each of three criteria (Betweenness Centrality (BC), Closeness Centrality (CC), and Degree Centrality (DC)), and is determined by using a Multi Criteria Decision Method (MCDM) based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Analytical Hierarchy Process (AHP) was applied to determine the weight coefficients of the mentioned criteria, and stations were ranked based on TOPSIS approach. The new proposed method outperforms other existing methods. The optimization methodology developed in this paper can help in decision-making for transportation policy-makers, planners, investors, and system users, is useful in maximizing the coverage of bike demand by optimizing the location of bike stations based on node importance, to determine if there is a need to build a new station or relocate an existing one, and to optimize the number of bike stations subject to budget constraints.