Route Optimization for Split Delivery of Military Supplies with UGVs, Drones, and Transport Vehicles under Wartime Conditions Using Genetic Algorithms

This paper studies optimizing supply routes to resupply points using future battlefield transport systems such as UGVs and drones, along with existing transport vehicles. Drones, being unmanned systems, offer high mobility but have limited payload capacity, while UGVs provide greater payload capacity but lower mobility. Transport vehicles offer very high payload capacity but significantly less mobility, and as manned systems, they can supply areas inaccessible to unmanned systems. Moreover, actual battlefields may present situations where certain transport systems cannot enter due to enemy threats, road destruction, electronic attacks, and other factors. Therefore, this study designs routes that minimize transportation time during supply operations by considering realistic constraints that may occur in future battlefields and reflecting the characteristics of each transport system. Additionally, we propose a genetic algorithm to demonstrate that large-scale problems can be solved within limited time during urgent wartime conditions.

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Publication Details

Journal
Journal of the Korea Institute of Military Science and Technology
Published
2025-04-05
DOI
https://doi.org/10.9766/kimst.2025.28.2.224
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
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article

Route Optimization for Split Delivery of Military Supplies with UGVs, Drones, and Transport Vehicles under Wartime Conditions Using Genetic Algorithms

Gigyeong Kim, Suhwan Kim
Journal of the Korea Institute of Military Science and Technology
Advanced Manufacturing and Logistics Optimization
article

Route Optimization for Split Delivery of Military Supplies with UGVs, Drones, and Transport Vehicles under Wartime Conditions Using Genetic Algorithms

Gigyeong Kim, Suhwan Kim
article en

Abstract

This paper studies optimizing supply routes to resupply points using future battlefield transport systems such as UGVs and drones, along with existing transport vehicles. Drones, being unmanned systems, offer high mobility but have limited payload capacity, while UGVs provide greater payload capacity but lower mobility. Transport vehicles offer very high payload capacity but significantly less mobility, and as manned systems, they can supply areas inaccessible to unmanned systems. Moreover, actual battlefields may present situations where certain transport systems cannot enter due to enemy threats, road destruction, electronic attacks, and other factors. Therefore, this study designs routes that minimize transportation time during supply operations by considering realistic constraints that may occur in future battlefields and reflecting the characteristics of each transport system. Additionally, we propose a genetic algorithm to demonstrate that large-scale problems can be solved within limited time during urgent wartime conditions.

Journal of the Korea Institute of Military Science and TechnologyVol. 28(2)
Openalex Percentile: Top 91%
Advanced Manufacturing and Logistics Optimization
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