多型号平车装载问题的混合遗传算法

铁路运输中的多车型平车装载问题就是要解决在保证安全运输的条件下，提高铁路运输资源的利用率，节省铁路运输资源，这属于NP-hard问题，遗传算法在求解NP-hard问题方面具有较好的优化效果。文中首先分析了平车装载问题的基本技术条件，然后在基本遗传算法和FFD算法的基础上，提出一种求解多车型平车装载问题的混合型遗传算法，并给出算法的编码方法、遗传算子的设计和适应度函数的定义。一方面通过引入染色体有效性判断与修正方法，有效解决了进化过程中的无效染色体问题；另一方面通过引入基因座信息熵来进行群体多样性的计算和控制，有效解决了进化中的局部最优问题，最后用实例验证了所提算法的有效性。

A Hybrid Genetic Algorithm for the Loading Problem of Multiple-type Flatcars

The loading problem of multiple-type flatcars is an important task in railway transportation, which is described as loading a set of equipment of different sorts into flatcars of the given types. Firstly, the basic technical conditions of flatcar-loading are is analyzed. Secondly, the loading problem of multiple-type flatcars is described. Thirdly, the decreasing algorithm, a heuristic method for the bin packing problem, is introduced into the simple genetic algorithm, and a hybrid genetic algorithm is proposed for solving the loading problem of multiple-type flatcars. In the hybrid genetic algorithm, the idea of the simple genetic algorithm is used to search the solution of the flatcars sequence, and the idea of first fitting the decreasing algorithm is used to load the equipment into the flatcars sequence obtained by the simple genetic algorithm. Fourthly, the method for judging and adjusting the chromosome validity is proposed to improve the ineffective chromosome, and the method for calculating, judging and adjusting the diversity of population by Calculation of the locus information entropy is introduced to Control the diversity of population. Finally, the effectiveness of the hybrid genetic algorithm is convinced by the computational results of an example.