Optimization of E-commerce Order Batching and Sequencing Considering Worker Fatigue

As competition in terms of order fulfillment timeliness among major e-commerce shopping platforms intensifies, improving order picking efficiency has become a key problem for e-commerce warehouses. Previous studies suggest that order batching strategies can enhance picking efficiency but overlook the fact that worker efficiency tends to decline with fatigue, leading to challenges in implementing the optimization results of batching and sequencing. A mixed integer programming model is developed to minimize the total order completion time. This model considers worker energy consumption while jointly optimizing worker rest batching, order batching and sequencing decisions. A two-stage algorithm and a control-based seed algorithm are developed, while their performance is compared and verified. Results show that the control-based seed algorithm is superior to the two-stage algorithm; the rest arrangement with consideration of worker fatigue can not only enhance employee satisfaction but also decrease the total order completion time. Sensitivity analysis reveals that when the work intensity difference between pickers and sorters increases or the buffer capacity becomes uncertain, the control-based seed algorithm exhibits superior effectiveness and stability.