Optimizing Cooperative Carrier-Vehicle Routing with Iterative Second-Order Cone Programming Method

This study focuses on optimizing a cooperative delivery system that combines a large-capacity but slow carrier and two fast yet capacity-limited unmanned aerial vehicles (UAVs). The primary objective is to minimize the carrier’s total travel time while ensuring all delivery points in predetermined order are serviced by the UAVs. We formulate this problem with an emphasis on the flight patterns of the two UAVs. We propose a novel optimization approach that breaks down the complex problem into manageable subproblems by considering pairs of UAV flights. This decomposition enables more efficient computation and better scalability than a prior approach. Numerical experiments demonstrate that in a test instance with 20 delivery points, our method reduces computation time by over 90% and decreases the carrier’s travel time by approximately 40% compared to an existing approach. These results suggest significant potential for improving the efficiency of cooperative delivery systems, which can be applied to logistics and various vehicle coordination problems.

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Publication Details

Journal
Annals of Operations Research
Published
2026-02-09
DOI
https://doi.org/10.1007/s10479-026-07089-x
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimizing Cooperative Carrier-Vehicle Routing with Iterative Second-Order Cone Programming Method

Maharani Rizki Larasati, I-Lin Wang, Makoto Yamashita, Ning-Wen Yang
Annals of Operations Research
UAV Applications and Optimization
article

Optimizing Cooperative Carrier-Vehicle Routing with Iterative Second-Order Cone Programming Method

Maharani Rizki Larasati, I-Lin Wang, Makoto Yamashita, Ning-Wen Yang
article en

Abstract

This study focuses on optimizing a cooperative delivery system that combines a large-capacity but slow carrier and two fast yet capacity-limited unmanned aerial vehicles (UAVs). The primary objective is to minimize the carrier’s total travel time while ensuring all delivery points in predetermined order are serviced by the UAVs. We formulate this problem with an emphasis on the flight patterns of the two UAVs. We propose a novel optimization approach that breaks down the complex problem into manageable subproblems by considering pairs of UAV flights. This decomposition enables more efficient computation and better scalability than a prior approach. Numerical experiments demonstrate that in a test instance with 20 delivery points, our method reduces computation time by over 90% and decreases the carrier’s travel time by approximately 40% compared to an existing approach. These results suggest significant potential for improving the efficiency of cooperative delivery systems, which can be applied to logistics and various vehicle coordination problems.

Annals of Operations Research
Tokyo Institute of Technology (JP), National Cheng Kung University (TW)
Ministry of Science and Technology, Taiwan, Japan Society for the Promotion of Science
Openalex Percentile: Top 63%
UAV Applications and Optimization
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