Joint optimization of order picking and delivery in ergonomic picking systems with due dates for sustainability and resilience

E-commerce platforms, driven by consumer demand for same-day or even half-day delivery, face challenges such as high order volumes with varying due dates, multiple picking stations, and multiple delivery regions. These challenges may lead to order tardiness and decreased efficiency and responsiveness of warehouse logistics. This study jointly optimizes order picking and delivery in ergonomic picking systems by addressing order assignment, sequencing, picking, and delivery operations while considering due dates and minimizing order tardiness and delivery costs. A mixed integer programming (MIP) model is formulated, and an improved knowledge-guided fruit fly optimization algorithm with the shortest waiting time rule (IKGFOA-SWT) as a heuristic solution procedure is developed to solve the problem. The IKGFOA-SWT comprises three modules including an order assignment and sequencing module using IKGFOA, an order picking module employing the SWT rule, and a batch delivery module balancing the delivery and tardiness costs. Computational experiments are conducted to validate the MIP model and evaluate the performance of IKGFOA-SWT. The benchmark experiment underscores the importance of integrating order picking and delivery operations within a unified scheduling framework rather than treating them as independent optimization tasks. The small-scale experiment verifies the effectiveness of IKGFOA-SWT in finding optimal solutions. The large-scale experiment demonstrates the superiority of IKGFOA-SWT in generating high-quality solutions. This study provides valuable managerial insights and practical tools for the optimization of warehouse logistics operations, and contributes to the new norms of supply chain sustainability and resilience.