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Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
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Esra?a Alkafaween, Ahmad Hassanat, Ehab Essa and Samir Elmougy
The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in the initial population is important in determining the final optimal ...
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Mao Nishira, Satoshi Ito, Hiroki Nishikawa, Xiangbo Kong and Hiroyuki Tomiyama
Delivery drones have been attracting attention as a means of solving recent logistics issues, and many companies are focusing on their practical applications. Many research studies on delivery drones have been active for several decades. Among them, exte...
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Chao-Feng Gao, Zhi-Hua Hu and Yao-Zong Wang
The hub-and-spoke network (HSN) design generally assumes direct transportation between a spoke node and its assigned hub, while the spoke?s demand may be far less than a truckload. Therefore, the total number of trucks on the network increases unnecessar...
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Yusef Ahsini, Pablo Díaz-Masa, Belén Inglés, Ana Rubio, Alba Martínez, Aina Magraner and J. Alberto Conejero
With the increasing demand for online shopping and home delivery services, optimizing the routing of electric delivery vehicles in urban areas is crucial to reduce environmental pollution and improve operational efficiency. To address this opportunity, w...
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Shuai Zhou, Zheng Wang, Longmei Li and Houpu Li
The precision and efficiency of multi-target path planning are crucial factors influencing the performance of anti-mine operations using unmanned underwater vehicles (UUVs). Addressing the inadequacies in computation time and solution quality present in ...
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Zheping Yan, Weidong Liu, Wen Xing and Enrique Herrera-Viedma
How an autonomous underwater vehicle (AUV) performs fully automated task allocation and achieves satisfactory mission planning effects during the search for potential threats deployed in an underwater space is the focus of the paper. First, the task assi...
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Michalis Mavrovouniotis, Maria N. Anastasiadou and Diofantos Hadjimitsis
Ant colony optimization (ACO) has proven its adaptation capabilities on optimization problems with dynamic environments. In this work, the dynamic traveling salesman problem (DTSP) is used as the base problem to generate dynamic test cases. Two types of ...
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Roberto Montemanni and Mauro Dell?Amico
Drones are currently seen as a viable way of improving the distribution of parcels in urban and rural environments, while working in coordination with traditional vehicles, such as trucks. In this paper, we consider the parallel drone scheduling travelin...
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Sílvia de Castro Pereira, Eduardo J. Solteiro Pires and Paulo B. de Moura Oliveira
A new algorithm based on the ant colony optimization (ACO) method for the multiple traveling salesman problem (mTSP) is presented and defined as ACO-BmTSP. This paper addresses the problem of solving the mTSP while considering several salesmen and keepin...
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