Structuring the Last Mile with ReActV: Tool-Augmented Delivery Planning with Verification
Year: 2026
Type: conference-paper
Abstract: Last-mile deliveries form a critical part of logistics and supply chain management across both business-to-business (B2B) and business-to-customer (B2C) segments. Fulfilment of such deliveries is frequently hindered by incomplete delivery instructions, unreliable location signals, language barriers, and ambiguous addresses. We propose ReActV (Reason–Act–Verify), a prompt engineering methodology inspired by the classical ReAct and Chain-of-Verification (CoVe) paradigms, by incorporating an explicit verification stage and deterministic tools within the prompting loop for grounding courier actions with structured operational context for Large Language Models (LLMs). We present a multi-agent prototype implemented with the DSPy framework and applied to a real-world dataset, which transforms free-form text delivery instructions into structured and actionable insights for couriers. Our focus is on combining stepwise reasoning, action tools and verification tools for delivery planning. The paper provides a comparative evaluation of ReActV against Zero-Shot, Chain-of-Thought-only, and ReAct baselines – with ReActV demonstrating strong performance in verification quality and delivery issue coverage. The proposed approach can be viewed as a context-aware adaptive assistant. It can help address logistics challenges under low-resource settings, particularly for novice couriers in the present-day gig economy, by providing practical insights to enrich human–AI collaboration during last-mile deliveries while improving customer satisfaction and reducing operational costs.
Institutions: Loughborough University, EPAM Systems (United States)
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7162201082