Assessment and Realization of the Benefits of Collaboration Among Ridesharing Service Providers Based on Metaheuristic Algorithms

As ridesharing is one of the emerging sustainable transport modes that has been widely adopted by commuters and travelers in cities, it has been extensively studied for over a decade. Although many research issues related to ridesharing have been studied, most studies focus on these issues in the context of single ridesharing service providers. However, the existence of multiple ridesharing service providers poses unaddressed research issues. In economics, collaboration might enable two companies to achieve greater market share and efficiency than they could achieve independently. “One plus one is greater than two” refers to the concept of synergy, where combining two elements creates a result that is more valuable or effective than the sum of their individual parts. An interesting question is whether multiple ridesharing service providers can benefit from collaboration. This study aims to assess and realize the benefits of collaboration among ridesharing service providers using metaheuristic algorithms. In this paper, we will study this research question based on two decision models: (1) Decision Model 1 for multiple independent ridesharing service providers and (2) Decision Model 2 for a Collaborative Ridesharing Service Provider. We formulated the optimization of these two decision models and developed twelve metaheuristic algorithms for the two decision models, and conducted experiments to study their effectiveness in terms of performance and computational efficiency. The results indicate that the benefits that can be realized depend critically on the type of metaheuristic algorithm used. The results of this study show that “one plus one is greater than two” holds for ridesharing if an effective solver is used.