基于效率和稳定性的智能RGV动态调度研究

摘要

随着电子商务的飞速发展, 对于仓储配送系统中RGV的调度问题提出了新的要求.建立基于效率和稳定性的智能RGV动态调度机制, 根据最小完成时间, 构建动态调度模型.通过改进的遗传算法对于数据处理的收敛速度较快, 并通过保留精英和随机抽样的方法, 使得优秀个体保留的概率增大, 有利于加快种群的收敛速度.利用MATLAB编程软件实证的方式, 深入分析智能RGV动态调度策略和作业效率, 并取得一定程度的优化效果, 具有相应的参考价值和借鉴依据.最后给出了模型和算法的客观评价.%With the rapid development of e-commerce, new requirements are put forward for the scheduling problem of RGV in warehouse distribution system. An intelligent RGV dynamic scheduling mechanism based on efficiency and stability is established, and a dynamic scheduling model is constructed based on the minimum completion time. The improved genetic algorithm has a faster convergence rate for data processing, and by retaining the elite and random sampling methods, the probability of retaining excellent individuals is increased, which is beneficial to speed up the convergence of the population. Using the MATLAB programming software to empirically analyze the intelligent RGV dynamic scheduling strategy and operational efficiency, and obtain a certain degree of optimization results, with corresponding reference value and reference. Finally, the objective evaluation and improvement methods of the model and algorithm are given.