Abstract
With the development of social urbanization, bike-sharing was born and developed rapidly. Many cities around the world believe that Shared bikes promote environmental protection and development towards sustainable society. In this paper, we consider two problems: bike-sharing system (BSS) redistribution efficiency maximization and system rebalance synchronize. Firstly, we describe BSS dynamic model with a linear form based on graph theory. Then, we propose a quantitative representation to measure the operational efficiency of BSS. We present a model predictive control (MPC) method to solve operational efficiency problem with system constraints. Both the dynamic state and the constraints in the redistribution are considered in MPC algorithm. Then, we verify the effectiveness of our proposed algorithm on different connection type BSS network. According to experimental results, the operational efficiency is maximized and BSS network can reach an equilibrium state during dynamic optimization. Compared to other methods, MPC approach is shown more effective.
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Chen, Y., Zeng, Y., Wu, J., Li, Q., Wu, Z. (2020). Balancing of Bike-Sharing System via Constrained Model Predictive Control. In: Zhang, H., Zhang, Z., Wu, Z., Hao, T. (eds) Neural Computing for Advanced Applications. NCAA 2020. Communications in Computer and Information Science, vol 1265. Springer, Singapore. https://doi.org/10.1007/978-981-15-7670-6_41
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DOI: https://doi.org/10.1007/978-981-15-7670-6_41
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