Capacity booking control and incentive strategy in the rental system based on driving behavior
ZHANG Lifeng1,2, MU Yinping1, FAN Pengying3
1. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China; 2. Department of Liberal Arts and Science, Chengdu College of University of Electronic Science and Technology of China, Chengdu 611731, China; 3. School of Economics, Beijing Technology and Business University, Beijing 100048, China
Abstract：Considering the transfer of the customers' behavior, this paper has builded a stochastic dynamic programming model to study dynamic booking capacity control in the car rental system. When the customers' driving behavior can be monitored by intelligent equipment, we have researched how the price subsidy policy affected the capacity booking control process and customers' behavior. Because of the higher dimension of the model, we have proposed two dynamic programming decomposition approaches. One decomposition has approached dynamic programming by daily (ADPD), the other has approached dynamic programming by periodicity (ADPP). Finally, numerical simulations have verified the effectiveness of the proposed algorithms. The finding gives the principal of the capacity booking control, and the conclusions are as follows:1) The expectation profit of ADPP gets closer to maximum expectation profit; 2) When the customers' behavior has not been changed, the expected total profit will not increase with the increase of subsidy; 3) When the subsidy strategy increases the possibility of choosing good behavior, the increase of subsidy will increase the expected total profit of the enterprise. The results will provide a support for capacity booking control in the car rental system.
张利凤, 慕银平, 樊鹏英. 考虑驾驶行为的租赁预订控制与激励策略研究[J]. 系统工程理论与实践, 2019, 39(7): 1690-1703.
ZHANG Lifeng, MU Yinping, FAN Pengying. Capacity booking control and incentive strategy in the rental system based on driving behavior. Systems Engineering - Theory & Practice, 2019, 39(7): 1690-1703.
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