A multiple type bike repositioning problem

Yanfeng Li, W. Y. Szeto*, Jiancheng Long, Chin Sum Shui

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    70 Scopus citations

    Abstract

    This paper investigates a new static bicycle repositioning problem in which multiple types of bikes are considered. Some types of bikes that are in short supply at a station can be substituted by other types, whereas some types of bikes can occupy the spaces of other types in the vehicle during repositioning. These activities provide two new strategies, substitution and occupancy, which are examined in this paper. The problem is formulated as a mixed-integer linear programming problem to minimize the total cost, which consists of the route travel cost, penalties due to unmet demand, and penalties associated with the substitution and occupancy strategies. A combined hybrid genetic algorithm is proposed to solve this problem. This solution algorithm consists of (i) a modified version of a hybrid genetic search with adaptive diversity control to determine routing decisions and (ii) a proposed greedy heuristic to determine the loading and unloading instructions at each visited station and the substitution and occupancy strategies. The results show that the proposed method can provide high-quality solutions with short computing times. Using small examples, this paper also reveals problem properties and repositioning strategies in bike sharing systems with multiple types of bikes.

    Original languageEnglish
    Pages (from-to)263-278
    Number of pages16
    JournalTransportation Research Part B: Methodological
    Volume90
    DOIs
    StatePublished - 1 Aug 2016

    Keywords

    • Greedy heuristic
    • Hybrid genetic algorithm
    • Mixed integer programming
    • Static bike repositioning problem

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