In the paper “Dynamic Relocations in Car-Sharing Networks,” researchers have developed a new dynamic car relocation policy aimed at improving the efficiency of car-sharing networks. The policy addresses the challenge of unpredictable and uneven demand across the network by projecting the classical fluid model onto the simpler dimension of relocation decisions. This projection leads to a clearer understanding of the fluid model as a set of linear programs. The effectiveness of this new dynamic policy has been rigorously tested against traditional static policies through extensive simulations. The results are promising, showing that the dynamic policy significantly outperforms its static counterpart, reducing the optimality gap by more than 23% on average. This breakthrough offers substantial potential benefits for car-sharing operations, enhancing their ability to respond adaptively to changing demand and thus optimizing resource allocation and user satisfaction.
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Hosseini et al. (2024) studied this question.
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