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Proposed Search Strategies Improve Computational Cost of Bicycle-Sharing Problem


A bicycle sharing system.

The popularity of bicycle sharing systems is expected to grow in the future.

Credit: Medium.com

Researchers at Japan's Tokyo University of Science (TUS) proposed two methods for reducing the computational cost of bicycle sharing systems without impacting performance. \

This involves rebalancing bikes among ports so users can always use them, while reducing labor costs and carbon emissions.

The proposed strategies search for approximate solutions to the multiple-vehicle bike sharing system routing problem with soft constraints (mBSSRP-S).

The first approach reduces the number of solutions approximating a solution to the optimization problem before finding a feasible answer, via the Or-opt and CROSS-exchange algorithms; the second approach alters the problem based on the feasible solution to either the original mBSSRP problem or the mBSSRP-S problem, then seeks near-optimal solutions by either Or-opt or CROSS-exchange.

"Once we calculated the feasible solution, we could find short travel times for the rebalancing vehicles quickly by solving the hard constraint problem, mBSSRP, instead of mBSSRP-S," said TUS' Tohru Ikeguchi.

From Tokyo University of Science (Japan)
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA


 

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