Abstract
Uncertain Capacitated Arc Routing Problem (UCARP) is a challenging optimization problem. Genetic Programming (GP) has been successfully applied to train routing policies (heuristics to make decisions in real time rather than a fixed solution) to respond to uncertain environments effectively. However, the effectiveness of routing policy is scenario dependent, and it takes time to train a new routing policy for each scenario. In this paper, we investigate GP with knowledge transfer to improve the training efficiency by reusing useful knowledge from previously solved related scenarios. We propose a novel knowledge transfer approach which our experimental results show that it obtained significantly higher training efficiency than the existing GP knowledge transfer methods, and the vanilla training process without knowledge transfer.
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Ansari Ardeh, M., Mei, Y., Zhang, M. (2019). A Novel Genetic Programming Algorithm with Knowledge Transfer for Uncertain Capacitated Arc Routing Problem. In: Nayak, A., Sharma, A. (eds) PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. Lecture Notes in Computer Science(), vol 11670. Springer, Cham. https://doi.org/10.1007/978-3-030-29908-8_16
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DOI: https://doi.org/10.1007/978-3-030-29908-8_16
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