A Hybrid and Adaptive Metaheuristic for the Rebalancing Problem in Public Bicycle Systems
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To meet the fluctuating demand for bicycles and for vacant lockers at each station, employees need to actively shift bicycles between stations by a fleet of vehicles. This is the rebalancing problem in public bicycle systems. In this paper, we propose a new objective function to the rebalancing problem, which meets the actual circs better. Then we explore a new method combines data mining process with GRASP-PR which incorporate GRASP and path-relinking procedure to experiment, not a single activation, but multiple and adaptive executions of the data mining process during the metaheuristic execution. And some improvements are made in some phases of the algorithm according to the feature of the bicycle rebalancing problem. Practice examples and comparison with the typical algorithm in the fields are made. The results show that the new proposals were able to find better results in less computational time for the rebalancing bicycle problem. The research result has been implemented in Hangzhou, China.
KeywordsPublic bicycle system Greedy randomized adaptive search procedure Path-relinking Data mining Bicycle rebalancing
This work was financially supported by Chinese National Natural Science Foundation(61572165) and Public Projects of Zhejiang Province(LGF18F030006).
- 5.Erdoğan, G., Laporte, G., & Calvo, R. W. (2013). The one commodity pickup and delivery traveling salesman problem with demand intervals. Technical Report CIRRELT-2013-46, MontrealGoogle Scholar
- 8.Papazek, P., Kloimüllner, C., Hu, B., Raidl, G.R.: Balancing bicycle sharing systems: an analysis of path relinking and recombination within a GRASP hybrid. Parallel Problem Solving from Nature – PPSN XIII. 8672, 792–801 (2014)Google Scholar
- 17.Angel-Bello, F.R., González-Velarde, J.L., Alvarez, A.M.: Greedy randomized adaptive search procedures. Metaheuristic Procedures for Training Neutral Networks, pp. 207–223. Springer (2006)Google Scholar
- 18.Glover, F., Laguna, M., Marti, R.: Scatter search and path relinking: advances and applications. Handbook of Metaheuristics, pp. 1–35. Kluwer Academic Publishers (2003)Google Scholar
- 19.Glover, F.: Multi-start and strategic oscillation methods — principles to exploit adaptive memory. Computing Tools for Modeling, Optimization and Simulation, pp. 1–23. Springer, Boston (2000)Google Scholar
- 21.Glover, F.: Tabu search and adaptive memory programming — advances, applications and challenges. Interfaces in Computer Science and Operations Research, pp. 1–75. Springer (1997)Google Scholar