Subscription & Per-Day Pricing vs Same-Day Service: A Simulation of Temporally Consolidated Delivery Systems

Abstract

Same day delivery is often viewed as the benchmark for last mile logistics because of its convenience and time savings, but its adoption as a wide spread service is limited by high costs. Orders vary between time and location, restricting economies of scale and often resulting in inefficient routes where multiple vehicles serve the same neighborhood within short intervals. To address these issues, this thesis introduces temporal consolidation, where deliveries are grouped and scheduled for specific days of the week or month. Using simulations of customers with different order behaviors and locations, we evaluate delivery scenarios that include grouping requests, optimizing travel routes, and adjusting delivery frequencies. Results show that consolidated deliveries reduce total travel distance compared with same day service. Customers are generally willing to accept longer consolidation periods when paired with cost savings, while higher delivery prices increase demand for faster service.