基于自适应遗传算法的电子商务物流配送及仿真研究

Electronic Commerce Logistics Distribution and Simulation Research on Based on Adaptive Genetic Algorithm

针对电子商务物流配送中遗传算法易陷入局部最优的不足,比较研究了在货车最大路程受限的约束条件下的物流配送效果,分析了自适应遗传算法和节约遗传算法在车辆配送模型中的性能,并通过仿真实验得到最优配送路径。仿真结果表明,自适应遗传算法能明显降低配送过程的总代价值,收敛速度快,克服了遗传算法和节约遗传算算法易陷入局部最优的不足,提高了配送模型的有效性和实用性。

In e-commerce logistics and distribution problems, according to the genetic algorithm is easy tofall into local optimum problem, in this paper the adaptive genetic algorithm are studied and compared underthe constraints of the maximum distance of truck is limited, adaptive genetic algorithm and conservationof genetic algorithm in vehicle deserves to send in the model performance analysis, and get the optimaldistribution route through the simulation experiment. The results indicate that the distribution of total valuesignificantly decreased the adaptive genetic algorithm and convergence speed fast, so as to overcome thegenetic algorithms and genetic economy calculate method is easy to fall into local optimal, and the validityand practicability of the distribution model is improved greatly, and played a guiding role in the practicalapplication.