铁路网多流向超限货物运输路径优化模型及算法

Routing Optimization Model and Algorithm for Out-of-Gauge Freights in Multiple Flow Railway Network

为了将铁路网中具有不同去向的超限货物合理地分配至各条路径,以超限货物的运输路径里程、运输时间以及对既有线路正常运营组织干扰最小为目标,以路段运输限界、通过能力和途经桥梁乘载能力为约束,建立多流向超限货物运输路径选择的多目标规划模型.根据模型特点设计多目标混合遗传算法进行求解,该算法采用自然数组编码方式以及特殊的交叉、变异算子用以满足约束条件,同时引入模拟退火策略提高邻域搜索能力.实例结果表明,对于包含14个节点车站、23个路段的复杂铁路网,利用本文模型算法获得方案的目标函数值均优于遗传算法和退火算法得到的方案,从而为铁路网超限货物运输路径选择提供技术决策方法.

In order to distribute the out-of-gauge freights reasonably to paths in railway network, a multi-objective optimization model was built for route selection of multi-direction out-of-gauge freights. In the model, the minimum transport route mileage, the minimum haulage time, and the minimum interference to the normal operation of the existing railway lines were taken as targets ; and the distance between railway out-of-gauge freights and structure gauge, the railway transport capacity, and the loading capacity of the bridge along the way were used as constraints. According to the model characteristics, a multi-objective hybrid genetic algorithm was proposed to solve the model. In the algorithm, the natural array coding mode, together with cross and mutation operators, were designed to fit the constraints, and a simulated annealing strategy was introduced to enhance its neighborhood search capability. In addition, the proposed method was applied to the complex network containing 14 node stations and 23 sections to verify its validity. The application results show that the objective function values obtained by the proposed model and algorithm are superior to those obtained by genetic algorithm and annealing algorithm. Therefore, this method provides a technical measure for the decision-making of path selection in out-of-gauge freights transportation.