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CAPACITATED LOCATION-ROUTING PROBLEM FOR A COMBINED MANNED-UNMANNED TEAMING SYSTEM USING LAGRANGIAN RELAXATION AND LOCATION-BASED HEURISTIC.

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Title: CAPACITATED LOCATION-ROUTING PROBLEM FOR A COMBINED MANNED-UNMANNED TEAMING SYSTEM USING LAGRANGIAN RELAXATION AND LOCATION-BASED HEURISTIC.
Authors: Jinho Lee1 jinholee@hongik.ac.kr
Source: International Journal of Industrial Engineering. 2025, Vol. 32 Issue 5, p1299-1317. 19p.
Subject Terms: *LOCATION problems (Programming), *MILITARY reconnaissance, *AUTONOMOUS vehicles, *LOGISTICS, *RESEARCH vessels, *RELAXATION methods (Mathematics)
Abstract: The integration of unmanned systems into modern military operations has heightened the importance of manned-unmanned teaming (MUM-T), particularly in maritime surveillance missions. This study addresses a critical challenge in MUM-T operations: Optimally locating manned surface vessels and assigning reconnaissance routes for unmanned surface vehicles (USVs) under capacity constraints. We formulate this model as a capacitated Location-Routing Problem and propose a two-phase solution framework. The first phase solves three variants of the facility location problem--the uncapacitated facility location problem, p-median problem, and capacitated facility location problem--using Lagrangian relaxation. The second phase applies a location-based heuristic to generate efficient routing plans for USVs. Computational experiments using benchmark datasets demonstrate the effectiveness of the proposed approach, particularly highlighting efficiency in the uncapacitated case. This study contributes to logistics planning for hybrid manned-unmanned systems by adapting classical optimization tools to military reconnaissance scenarios. [ABSTRACT FROM AUTHOR]
Database: Academic Search Index
Description
Abstract:The integration of unmanned systems into modern military operations has heightened the importance of manned-unmanned teaming (MUM-T), particularly in maritime surveillance missions. This study addresses a critical challenge in MUM-T operations: Optimally locating manned surface vessels and assigning reconnaissance routes for unmanned surface vehicles (USVs) under capacity constraints. We formulate this model as a capacitated Location-Routing Problem and propose a two-phase solution framework. The first phase solves three variants of the facility location problem--the uncapacitated facility location problem, p-median problem, and capacitated facility location problem--using Lagrangian relaxation. The second phase applies a location-based heuristic to generate efficient routing plans for USVs. Computational experiments using benchmark datasets demonstrate the effectiveness of the proposed approach, particularly highlighting efficiency in the uncapacitated case. This study contributes to logistics planning for hybrid manned-unmanned systems by adapting classical optimization tools to military reconnaissance scenarios. [ABSTRACT FROM AUTHOR]
ISSN:10724761
DOI:10.23055/ijietap.2025.32.5.10347