Current and emerging formulations and models of real-life rich vehicle routing problems

Widuch, Jacek

doi:10.1016/b978-0-12-815715-2.00006-3

Cited by 4 publications

(5 citation statements)

References 146 publications

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“…The choice of population size should consider the problem complexity and available computational resources. The crossover rate represents the probability of performing a crossover operation between two parent routes to generate offspring [31]. A higher crossover rate promotes the exploration and diversification of the solution space.…”

Section: Ga Parameters and Tuningmentioning

confidence: 99%

“…These solutions represent trade-offs between the different objectives, allowing decision makers to choose the most suitable routing strategies based on their preferences and priorities. Moreover, GAs enable the exploration of a large solution space, providing a more comprehensive search for optimal or near-optimal solutions [31]. The use of crossover and mutation operators facilitates the creation of new routes by combining and modifying existing ones, introducing diversity and preventing premature convergence to suboptimal solutions.…”

Section: Benefits Of Gas In Electric and Flying Vehicle Routingmentioning

confidence: 99%

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Multi-Objective Routing Optimization in Electric and Flying Vehicles: A Genetic Algorithm Perspective

Alolaiwy,

Hawsawi,

Zohdy

et al. 2023

Applied Sciences

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The advent of electric and flying vehicles (EnFVs) has brought significant advancements to the transportation industry, offering improved sustainability, reduced congestion, and enhanced mobility. However, the efficient routing of messages in EnFVs presents unique challenges that demand specialized algorithms to address their specific constraints and objectives. This study analyzes several case studies that investigate the effectiveness of genetic algorithms (GAs) in optimizing routing for EnFVs. The major contributions of this research lie in demonstrating the capability of GAs to handle complex optimization problems with multiple objectives, enabling the simultaneous consideration of factors like energy efficiency, travel time, and vehicle utilization. Moreover, GAs offer a flexible and adaptive approach to finding near-optimal solutions in dynamic transportation systems, making them suitable for real-world EnFV networks. While GAs show promise, there are also limitations, such as computational complexity, difficulty in capturing real-world constraints, and potential sub-optimal solutions. Addressing these challenges, the study highlights several future research directions, including the integration of real-time data and dynamic routing updates, hybrid approaches with other optimization techniques, consideration of uncertainty and risk management, scalability for large-scale routing problems, and enhancing energy efficiency and sustainability in routing. By exploring these avenues, researchers can further improve the efficiency and effectiveness of routing algorithms for EnFVs, paving the way for their seamless integration into modern transportation systems.

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Section: Ga Parameters and Tuningmentioning

confidence: 99%

Section: Benefits Of Gas In Electric and Flying Vehicle Routingmentioning

confidence: 99%

Multi-Objective Routing Optimization in Electric and Flying Vehicles: A Genetic Algorithm Perspective

Alolaiwy,

Hawsawi,

Zohdy

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Beyond the humanitarian operation's scope, but related to this study, ref. [11] addressed the eco-friendly, unmanned bus routing problem, while [12] proposed and reviewed various RVRP within the field. Ref.…”

Section: Previous Review Papersmentioning

confidence: 99%

Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches

et al. 2021

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The growing field of humanitarian operations is driven by frequent events of disasters seen in the world today. Within this field, Operations Research (OR) plays a critical role in alleviating the suffering of victims that are impacted by disasters. This paper focuses on the branch of a well-known OR problem, known as the Vehicle Routing Problem (VRP), within the selected scope of humanitarian operations. A total of 123 papers of the last decade are reviewed and classified under the humanitarian operations of supply and delivery, evacuation as well as rescue operations. Besides specific disaster management phases and disaster types, various modelling challenges are highlighted, hinting towards a richer and more complex VRP seen under selected model characteristic classifications. Furthermore, established solution approaches, including hybrid solutions, are highlighted and classified, discussing how they are applied in the context of these humanitarian operations. The inclusion of a machine learning solution approach under the same classification is proposed. Finally, the trend and future outlook of VRP for the suggested humanitarian operations are discussed and highlighted.

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“…It involves designing and developing systems that optimize EV usage, manage charging infrastructure, and provide real-time information to drivers while ensuring reliability, efficiency, and security. Software engineering practices, such as requirements analysis, design, and testing, are essential in creating effective ITS solutions for EVs in smart cities [14,15]. By leveraging these practices, developers can create software systems that optimize transportation resources, promote environmental sustainability, and enhance the overall quality of life of urban residents.…”

Section: Introductionmentioning

confidence: 99%

Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles

Alanazi,

Alenezi

2023

Applied Sciences

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As the process of urbanization continues to accelerate, the demand for sustainable cities has become more critical than ever before. The incorporation of electric vehicles (EVs) is a key component in creating sustainable cities. However, the development of smart cities for EVs entails more than just the installation of charging stations. Software engineering plays a crucial role in realizing smart cities for electric vehicles. This paper examines the role of software engineering in the creation of smart cities for electric vehicles, the techniques utilized in electric vehicle charging infrastructure, the obstacles faced by software engineers, and the future of software engineering in sustainable cities. Specifically, the paper explores the significance of software engineering in integrating EVs into the transportation system, including the design of smart charging and energy management systems, and the establishment of intelligent transportation systems. Additionally, the paper offers case studies to demonstrate successful software engineering implementations for smart cities. Finally, the paper concludes with a discussion of the challenges that software engineers encounter in implementing intelligent transportation systems for EVs and provides future directions for software engineering in sustainable cities.

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Current and emerging formulations and models of real-life rich vehicle routing problems

Cited by 4 publications

References 146 publications

Multi-Objective Routing Optimization in Electric and Flying Vehicles: A Genetic Algorithm Perspective

Multi-Objective Routing Optimization in Electric and Flying Vehicles: A Genetic Algorithm Perspective

Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches

Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles

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