铁路罐式集装箱空箱调配优化模型及遗传模拟退火算法

针对罐式集装箱运输的特殊性,考虑重箱流和空箱流调配的综合优化,以罐箱运输费用最小为目标,建立铁路罐式集装箱空箱调配优化多商品网络流模型,并构造了1种嵌入模拟退火操作的遗传算法对之进行求解。为了使模型与算法可得到更符合实际、操作性更强的结果,给出了3种空罐箱调配的策略,作为隐含条件加入到算法求解过程中。利用自适应遗传模拟退火算法对随机生成的实际规模问题算例进行求解,并与用通用代数建模系统软件GAMS的计算结果进行对比。结果表明,前者得出的结果与最优解差距不大,而且运算速度更快,更能满足解决实际问题的需要,为铁路罐箱调配优化提供了良好的决策支持模型和算法。

Optimization Model of Railway Empty Tank Container Allocation and Genetic Simulated Annealing Algorithm

Aiming at the particularity of tank container transportation and considering the comprehensive optimization of loading container and empty container,the paper proposes a multi-commodity network flow model for railway tank container distribution optimization with the minimum transportation cost as the target.A hybrid genetic algorithm embedded with simulated annealing operation is constructed to work out the solutions.Three empty container allocation strategy is presented,which is added in the solving process of the algorithm as the implied condition,so as to make the model as well as the algorithm obtain more practical and maneuverable results.Adaptive genetic simulated annealing algorithm is adopted to work out the solutions for several randomly generated examples with real size,and compared with GAMS results.It indicates that there is little difference between the result obtained by the former method and the optimal solution.Moreover,the calculation speed of the former method is faster and it can better meet the requirement for solving practical problems and thus an optimal decision-making support model and algorithm is provided for the optimization of railway tank container allocation.