Abstract: Considering the uncertainty of regional public logistics centers (RPLC), the paper presents a bi-level programming model for the optimal location of RPLC based on scenario planning,. The upper-level model determines the optimal location by minimizing the construction and operation cost; the lower-level model is a multi-vehicle-type stochastic user equilibrium model with determined demand. When OD and other variables for every scenario are predicted, corresponding location results can be obtained based on the bi-level programming model, and the location result which can minimize the weighted average cost of all scenarios is chosen as the best solution. A discrete particle swarm algorithm is proposed to solve the bi-level programming model. Finally, a numerical example is given to illustrate that the model and the discrete particle swarm method is feasible and effective to decrease the RPLC construction and operation cost and the investment risk.

Key words: location of public logistics centers, scenario planning, bi-level programming, discrete particle swarm algorithm

摘要： 针对区域公共物流中心(Regional Public Logistics Center, RPLC)选址问题，考虑到选址问题的不确定性，运用场景规划技术，建立RPLC选址双层规划模型。上层规划模型最小化RPLC建设及运营费用，下层建立分车型随机用户均衡模型用以描述城市内车辆的路径选择。通过预估RPLC在未来运营中可能出现的各种场景，确定相应场景下变量的取值，并求解双层规划模型、确定该场景下的最优选址结果；根据场景发生的概率选取在各种场景下加权平均费用最小的选址结果作为最终结果。同时，本文给出了求解该问题的离散粒子群算法和数值算例。结果表明，所建立的模型和求解算法是有效的，能较好地解决RPLC选址的不确定性，这对于节约RPLC建设和运营成本，减少投资风险是可行的。

关键词: 公共物流中心选址, 场景规划, 双层规划, 离散粒子群算法