基于遗传算法的单车运输配载研究

Study on Single Truck Loading of Transportation Based on Genetic Algorithm

单车配载优化问题是一个复杂的组合优化问题,属于NP-hard问题,即使在运输量较小时也很难得到最优解。针对此问题,建立了单车多型配载模型,将逐次放置货物的放置方式和遗传算法相结合,采用与布局方式相结合的解码过程和加速收敛的适应度函数。通过实验比较得到车厢面积占有率、优化时间以及相应算法参数值。结果表明,该算法较其他算法有更好的车厢空间利用率和快速优化能力,有效解决了一般遗传算法优化时间长的问题,对实际公路运输配载优化问题有一定的参考价值。

Single truck loading is a complicated combinatorial optimization problem, which belongs to NP - hard problems. It is hard to find the optional solution even if the amount is not large. Focusing on this issue, this paper builds a loading problem model with several types of goods in single truck, which connects the placement mode to genetic algorithm and adopts the decoding process combining with the way of placing goods and the fitness function to accelerate optimization convergence. This paper obtains room area utilization rate and optimization time and parameters of algorithm through experiment. The result shows that this algorithm has better room utilization rate and fast optimization competence, which solves the problem of long - time optimization of genetic algorithm effectively. And it can be taken as a reference in some sense to practical highway transportation loading optimization problem.