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A two-phase heuristic approach to the bike repositioning problem

机译：自行车重新定位问题的两相启发式方法

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An approach to overcome the bike imbalance problem is to transfer excess bikes to branches with bike shortages. This study develops a constrained mathematical model to deal with a multi-vehicle bike-repositioning problem, and aims to minimize the sum of transportation and unmet demand costs over a planning horizon through bike-transfer strategies under a minimum service requirement. A two-phase heuristic based on linear programming was proposed to solve the problem and produce compromising solutions. In the first phase, the paper developed a linear programming model to quickly develop decisions related to bike inventory, unloading, and loading for all stations for each time slot. In the second phase, this paper proposed an iterative approach through two parameter sensitive mathematical models to sequentially reduce the problem scale to develop decisions related to bike transfers. Computational results show that the proposed approach is superior to a CPLEX optimizer and a hybrid heuristic based on a genetic algorithm. The proposed approach was used to analyze the bicycle system in Taiwan. The impacts of various system parameters on the system were also investigated. (C) 2019 Elsevier Inc. All rights reserved.
机译：克服自行车不平衡问题的方法是将多余的自行车转移到带自行车短缺的分支机构。本研究开发了一个受限制的数学模型来处理多车辆自行车排雷问题，并旨在通过最低服务要求通过自行车转移策略在规划地平线上最大限度地减少运输和未满足的成本。提出了一种基于线性编程的两相启发式，以解决问题并产生妥协解决方案。在第一阶段，本文开发了一种线性编程模型，可以快速制定与每次时隙的所有站点的自行车库存，卸载和加载相关的决策。在第二阶段，本文提出了一种迭代方法，通过两个参数敏感的数学模型来顺序地减少问题规模，以制定与自行车传输相关的决策。计算结果表明，该方法优于基于遗传算法的CPLEX优化器和混合启发式。拟议的方法用于分析台湾的自行车系统。还研究了各种系统参数对系统的影响。 （c）2019 Elsevier Inc.保留所有权利。

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