Integrating 5PL Frameworks with Drone-Based Last-Mile Delivery: A Model for Future-Ready Logistics

The rapid evolution of logistics service providers from 1PL to 5PL has underscored the growing need for intelligent, data-driven orchestration across the supply chain. Simultaneously, drone-based delivery has emerged as a promising solution to last-mile challenges, particularly in urban congestion zones and infrastructure-deficient rural areas. However, current deployments of drone logistics remain largely siloed and unintegrated with broader digital logistics platforms. This paper proposes a novel conceptual framework that embeds drone-based last-mile delivery within the orchestration architecture of fifth-party logistics (5PL) systems. Leveraging a multi-agent digital twin model, the study integrates technologies such as IoT for real-time tracking, AI-based metaheuristics (ALNS, PSO, NSGA-II) for route and hub optimization, and blockchain for SLA compliance. A simulation case based on India’s rural healthcare supply chain and ONDC clusters demonstrates substantial improvements in delivery time (↓65%), operational cost (↓40%), and carbon footprint (↓90%) over conventional 4PL systems. Sensitivity analyses under weather fluctuations, demand surges, and battery degradation validate the model’s resilience and adaptability. The findings position 5PLs as future-ready orchestrators of autonomous delivery systems and offer actionable insights for policymakers, supply chain managers, and technology developers toward building sustainable and scalable drone logistics ecosystems.The framework emphasizes interoperability and modular deployment, ensuring ease of integration with evolving logistics platforms.

Authors

Publication Details

Journal
Transportation Development Research
Published
2025-06-30
DOI
https://doi.org/10.55121/tdr.v3i1.449
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating 5PL Frameworks with Drone-Based Last-Mile Delivery: A Model for Future-Ready Logistics

Tejinder Singh Lakhwani
Transportation Development Research
Advanced Manufacturing and Logistics Optimization
article

Integrating 5PL Frameworks with Drone-Based Last-Mile Delivery: A Model for Future-Ready Logistics

Tejinder Singh Lakhwani
article en

Abstract

The rapid evolution of logistics service providers from 1PL to 5PL has underscored the growing need for intelligent, data-driven orchestration across the supply chain. Simultaneously, drone-based delivery has emerged as a promising solution to last-mile challenges, particularly in urban congestion zones and infrastructure-deficient rural areas. However, current deployments of drone logistics remain largely siloed and unintegrated with broader digital logistics platforms. This paper proposes a novel conceptual framework that embeds drone-based last-mile delivery within the orchestration architecture of fifth-party logistics (5PL) systems. Leveraging a multi-agent digital twin model, the study integrates technologies such as IoT for real-time tracking, AI-based metaheuristics (ALNS, PSO, NSGA-II) for route and hub optimization, and blockchain for SLA compliance. A simulation case based on India’s rural healthcare supply chain and ONDC clusters demonstrates substantial improvements in delivery time (↓65%), operational cost (↓40%), and carbon footprint (↓90%) over conventional 4PL systems. Sensitivity analyses under weather fluctuations, demand surges, and battery degradation validate the model’s resilience and adaptability. The findings position 5PLs as future-ready orchestrators of autonomous delivery systems and offer actionable insights for policymakers, supply chain managers, and technology developers toward building sustainable and scalable drone logistics ecosystems.The framework emphasizes interoperability and modular deployment, ensuring ease of integration with evolving logistics platforms.

Transportation Development ResearchVol. 3(1)
Openalex Percentile: Top 78%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.