Abstract
Logistics providers constantly face the challenge of improving turnaround time and warehouse product flow while simultaneously managing customer costs and maintaining a reliable workforce. To address this demand, this study proposes a simulation-optimization approach using Integer Programming (IP) models to optimize delivery scheduling under two distinct service regimes: fee-based and non-fee-based. Utilizing a real-world third-party logistics (3PL) business case, we demonstrate the models' capability to optimize logistical operations in dynamic environments. Specifically, we quantify the service cost and labor utilization efficiency across various demand patterns and tight capacity scenarios. This analysis evaluates the critical tradeoffs between labor cost, worker utilization, scheduling flexibility, and delivery performance. Our findings not only showcase the benefits and flexibility of the proposed model but also contribute significantly to the logistics optimization literature by highlighting the superior performance of the with fee model in terms of delivery commitment, worker satisfaction, and overall profit potential.
Recommended Citation
Wang, Haibo; Wang, Wendy; and Watson, Jason, "Optimization Simulation to Improve Product Delivery Scheduling" (2025). Proceedings of the 2025 Pre-ICIS SIGDSA Symposium. 74.
https://aisel.aisnet.org/sigdsa2025/74