Feb 19, 2021 · This paper presents a first, comprehensive review of hybrid methods that combine analytical techniques with ML tools in addressing VRP problems.
His main research work lies in artificial intelligence and machine learning. Notably, it focuses on adaptive control (reinforcement learning, Markov decision ...
Analytics and Machine Learning in Vehicle Routing Research
www.researchgate.net › publication › 34...
Feb 19, 2021 · The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and ...
Analytics and machine learning in vehicle routing research
www.researchgate.net › publication › 35...
Jan 12, 2022 · An Overview and Experimental Study of Learning-Based Optimization Algorithms for the Vehicle Routing... ... The vehicle routing problem (VRP) is a ...
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A first, comprehensive review of hybrid methods that combine analytical techniques with ML tools in addressing VRP problems concludes that ML can be ...
Abstract. The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms ...
Jul 16, 2024 · Vehicle routing is one of the most well-understood, extensively studied problems in both history and academia—it's been studied by academics ...
Oct 31, 2023 · The object of this research is a combinatorial optimization problem arising in the problem of the route of goods delivery vehicles.
Joe, Waldy, and Hoong Chuin Lau. 2020. “Deep reinforcement learning approach to solve dynamic vehicle routing problem with stochastic customers.” In Proceedings ...
Jul 24, 2023 · This study proposes a machine-learning model that exploits the graphical nature of VRP to design and improve evolutionary computational methods.