Dynamic Energy And Cost Efficient Multi-UAV Routing Problem Using Enhanced Genetic Algorithm

Alparslan Güzey; Mehmet Hakan Satman

Makale detayları

Dynamic Energy And Cost Efficient Multi-UAV Routing Problem Using Enhanced Genetic Algorithm

Yazarlar:

Alparslan Güzey | Mehmet Hakan Satman

Yayıncı:

Ankara Yildirim Beyazit University

Ana Başlıklar:

Industrial Engineering

Dergi:

Journal of Optimization and Decision Making Vol.3 Issue 2, pp.449-484

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001337688

pISSN:

2822-6410

Anahtar kelimeler:

Özet:

 In this study we propose a novel method for capacitated multi-UAV multi-visit routing problem. Our main focus is on achieving energy and cost effectiveness by using an enhanced genetic algorithm. We delve into the adjustment of UAV speeds based on payloads and study how it impacts energy consumption and operational expenses. Our comprehensive model takes into account the relationships between payload mass, UAV velocity and power usage providing a roadmap for modern UAV delivery networks. Through testing we have demonstrated that our approach can handle the challenges posed by real world delivery scenarios showcasing its adaptability in managing various payload sizes and navigating complex routes. Our research not only confirms that our algorithm is flexible and capable of optimizing UAV delivery operations but also fills a research gap by incorporating speed variability and payload differences in the optimization process. This study marks progress, in enhancing the efficiency of UAV based logistics by reducing both energy requirements and costs.

 In this study we propose a novel method for capacitated multi-UAV multi-visit routing problem. Our main focus is on achieving energy and cost effectiveness by using an enhanced genetic algorithm. We delve into the adjustment of UAV speeds based on payloads and study how it impacts energy consumption and operational expenses. Our comprehensive model takes into account the relationships between payload mass, UAV velocity and power usage providing a roadmap for modern UAV delivery networks. Through testing we have demonstrated that our approach can handle the challenges posed by real world delivery scenarios showcasing its adaptability in managing various payload sizes and navigating complex routes. Our research not only confirms that our algorithm is flexible and capable of optimizing UAV delivery operations but also fills a research gap by incorporating speed variability and payload differences in the optimization process. This study marks progress, in enhancing the efficiency of UAV based logistics by reducing both energy requirements and costs.

 In this study we propose a novel method for capacitated multi-UAV multi-visit routing problem. Our main focus is on achieving energy and cost effectiveness by using an enhanced genetic algorithm. We delve into the adjustment of UAV speeds based on payloads and study how it impacts energy consumption and operational expenses. Our comprehensive model takes into account the relationships between payload mass, UAV velocity and power usage providing a roadmap for modern UAV delivery networks. Through testing we have demonstrated that our approach can handle the challenges posed by real world delivery scenarios showcasing its adaptability in managing various payload sizes and navigating complex routes. Our research not only confirms that our algorithm is flexible and capable of optimizing UAV delivery operations but also fills a research gap by incorporating speed variability and payload differences in the optimization process. This study marks progress, in enhancing the efficiency of UAV based logistics by reducing both energy requirements and costs.

 In this study we propose a novel method for capacitated multi-UAV multi-visit routing problem. Our main focus is on achieving energy and cost effectiveness by using an enhanced genetic algorithm. We delve into the adjustment of UAV speeds based on payloads and study how it impacts energy consumption and operational expenses. Our comprehensive model takes into account the relationships between payload mass, UAV velocity and power usage providing a roadmap for modern UAV delivery networks. Through testing we have demonstrated that our approach can handle the challenges posed by real world delivery scenarios showcasing its adaptability in managing various payload sizes and navigating complex routes. Our research not only confirms that our algorithm is flexible and capable of optimizing UAV delivery operations but also fills a research gap by incorporating speed variability and payload differences in the optimization process. This study marks progress, in enhancing the efficiency of UAV based logistics by reducing both energy requirements and costs.

Makale detayları

Dynamic Energy And Cost Efficient Multi-UAV Routing Problem Using Enhanced Genetic Algorithm

Yazarlar:

Alparslan Güzey | Mehmet Hakan Satman

Yayıncı:

Ankara Yildirim Beyazit University

Ana Başlıklar:

Industrial Engineering

Dergi:

Journal of Optimization and Decision Making Vol.3 Issue 2, pp.449-484

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001337688

pISSN:

2822-6410

Capacitated Multi-UAV Routing

Energy Efficiency

Enhanced Genetic Algorithm

UAV Speed Dynamism

Sayı

Makale detayları

Dynamic Energy And Cost Efficient Multi-UAV Routing Problem Using Enhanced Genetic Algorithm

Yazarlar: Alparslan Güzey | Mehmet Hakan Satman

Yayıncı: Ankara Yildirim Beyazit University

Ana Başlıklar: Industrial Engineering

Dergi: Journal of Optimization and Decision Making Vol.3 Issue 2, pp.449-484

Belge Tipi: Makale

Yayın Tarihi: 12/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001337688

pISSN: 2822-6410

Capacitated Multi-UAV Routing

Energy Efficiency

Enhanced Genetic Algorithm

UAV Speed Dynamism

Sayı

Yazarlar:

Alparslan Güzey | Mehmet Hakan Satman

Yayıncı:

Ankara Yildirim Beyazit University

Ana Başlıklar:

Industrial Engineering

Dergi:

Journal of Optimization and Decision Making Vol.3 Issue 2, pp.449-484

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001337688

pISSN:

2822-6410