Genetic Programming With Knowledge Transfer and Guided Search for Uncertain Capacitated Arc Routing Problem

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@Article{Ardeh:2022:ieeeTEC,

• author = "Mazhar {Ansari Ardeh} and Yi Mei and Mengjie Zhang",
• title = "Genetic Programming With Knowledge Transfer and Guided Search for Uncertain Capacitated Arc Routing Problem",
• journal = "IEEE Transactions on Evolutionary Computation",
• year = "2022",
• volume = "26",
• number = "4",
• pages = "765--779",
• month = aug,
• keywords = "genetic algorithms, genetic programming",
• ISSN = "1089-778X",
• DOI = "doi:10.1109/TEVC.2021.3129278",
• abstract = "The uncertain capacitated arc routing problem has many real-world applications in logistics domains. Genetic programming (GP) is a promising approach to training routing policies to make real-time decisions and handle uncertain events effectively. In the real world, there are various problem domains and no single routing policy can work effectively in all of them. Instead of training in isolation, we can leverage the relatedness between the problems and transfer knowledge from previously solved source problems to solve the target problem. The existing transfer methods are not effective enough due to the loss of diversity during the knowledge transfer. To increase the diversity of the transferred knowledge, in this article, we propose a novel GP method that removes phenotypic duplicates from the source individuals to initialize the target individuals. Furthermore, assuming that the transferred knowledge used in initialization already includes all the important knowledge ex",
• notes = "also known as \cite{9621218}",

}

Genetic Programming entries for Mazhar Ansari Ardeh Yi Mei Mengjie Zhang

Citations