效率与人工负荷权衡下的中小型电商仓储人机动态调度优化

Optimization of Man-Machine Dynamic Scheduling for Small and Medium-Sized E-Commerce Warehousing under the Trade-Off of Efficiency and Labor Load

摘要: 针对中小型电商仓储面对订单波动时，由于资源弹性不足而出现的效率与人工负荷平衡困难问题，本研究突破传统半动态分区规则局限，以混合处理区为决策核心，设计全动态任务分配机制。该机制综合订单属性、资源位置及负载等多种因素，构建以最小化系统最大完工时间和人工总工作时间为目标的双目标优化模型，采用基于NSGA-II算法的求解框架得到帕累托最优解集。实验表明，与传统半动态规则相比，所提方法在保持系统效率相当的同时，实现了人工负荷的显著降低，验证了全动态分配机制在平衡效率与人工负荷这两个目标上的优越性，为资源受限下的中小型电商仓储调度提供了新方案。

Abstract: Aiming at the difficulty of balancing efficiency and labor load due to insufficient resource elasticity when small and medium-sized e-commerce warehousing faces order fluctuations, this research breaks through the limitations of traditional semi-dynamic zoning rules and designs fully dynamic tasks with the mixed processing area as the decision-making core. Allocation mechanism. This mechanism integrates multiple factors such as order attributes, resource location and load to build a dual-objective optimization model with the goals of minimizing the maximum system completion time and total labor working time, Pareto optimal solution set is obtained by using the framework of NSGA-II algorithm. Experiments show that compared with traditional semi-dynamic rules, the proposed method achieves a significant reduction in labor load while maintaining equivalent system efficiency, verifying the superiority of the fully dynamic allocation mechanism in balancing efficiency and labor load goals, and provides a new solution for small and medium-sized e-commerce warehousing scheduling under resource constraints.