Hybrid Genetic Algorithm Based on Machine Learning and Fitness Function Estimation Proposal for Ground Vehicle and Drone Cooperative Delivery Problem
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Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, the development of a hybrid genetic algorithm, integrating machine learning and function estimation, presents a novel approach to address the simultaneous intervention challenge involving unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs). The adaptability of this hybrid genetic algorithm confers a notable advantage in managing drone scenarios. Notably, this work constitutes the inaugural attempt in the literature to devise an exact solution for the concurrent intervention of a UGV and a UAV, with the added innovation of minimizing intervention time. This pioneering methodology holds promise for extending the problem domain to encompass more realistic scenarios, thereby bridging a significant gap in the literature and furnishing a foundational framework for future research endeavors. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Açıklama
Anahtar Kelimeler
Fitness function estimation, Hybrid genetic algorithm, Machine learning, Traveling salesman person, Vehicle routing problem with drone
Kaynak
Intelligent Systems Reference Library
WoS Q Değeri
Scopus Q Değeri
Q2
Cilt
260
