- author = "Shaolin Wang",
- title = "Explainable Genetic Programming for Evolving Routing Policies of Uncertain Capacitated Arc Routing Problems",
- school = "School of Engineering and Computer Science, Victoria University of Wellington",
- year = "2023",
- address = "New Zealand",
- month = "28 " # sep,
- keywords = "genetic algorithms, genetic programming, MOGP, PSO, GPHH, UCARP, TSMOGP-a, LGRE, Explainable Artificial Intellengence, XAI, Evolutionary Computation, Hyper Heuristic, Computer Science",
-
URL = "
https://openaccess.wgtn.ac.nz/articles/thesis/Explainable_Genetic_Programming_for_Evolving_Routing_Policies_of_Uncertain_Capacitated_Arc_Routing_Problems/24208311",
-
URL = "https://openaccess.wgtn.ac.nz/ndownloader/files/42487968",
-
DOI = "
doi:10.26686/wgtn.24208311",
- size = "279 pages",
- abstract = "he Uncertain Capacitated Arc Routing Problem (UCARP) is a well-known combinatorial optimization problem that has many real-world applications. Genetic programming has successfully evolved routing policies that can make real-time routing decisions for uncertain arc routing problems. Although the evolved routing policies are highly effective, they are typically very complex thus hard for real users to understand and trust. Therefore, it is necessary to improve the interpretability of GP-evolved routing policies.",
-
notes = "Also known as \cite{Wang2023}
Supervisors: Yi Mei and Mengjie Zhang",
