基于遗传算法的集装箱单箱三维装载优化问题

研究应用改进遗传算法优化铁路集装箱单箱三维装箱问题,达到充分利用集装箱装载质量或装载容积的目的。改进遗传算法中考虑货物放置方向、装载容积、装载质量及装载重心等约束条件,并结合方向及顺序约束采用巧妙的个体编码方法,结合装载容积、装载质量及重心约束构造合理的适应值函数。以16件货物装入20英尺箱为实例,应用改进遗传算法进行计算,计算结果为集装箱装载容积利用率为63 18%,并且可以缩短计算时间一半以上。

Optimization Based on Genetic Algorithm for Three-dimensional Packing in a Single Container

This paper studies the method of how to use the improved generic algorithm to optimize 3-D packing in a single container for railway transportation so that the loading mass or capacity of a container can be made use of to its fullest extent. The improved generic algorithm takes into account the direction in which the goods are placed, the loading capacity, the loading mass, the center of gravity of the load and other constraints. Combining the direction and sequence of placement, the algorithm uses a smart individual coding method and combining loading capacity, mass and gravity center of the load, the algorithm works out an appropriate function of adaptive value. An example is given in which 16 pieces of goods are loaded into a 20-foot container. The use of an improved generic algorithm for calculation shows that a usability of container volume of 63. 18% and that the time required by calculation can be reduced to over half of the time previously required.