1 code implementation • 3 Apr 2020 • Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay
We propose a policy gradient algorithm to learn a stochastic policy that selects 2-opt operations given a current solution.
no code implementations • 17 Jul 2019 • Dylan Rijnen, Jason Rhuggenaath, Paulo R. de O. da Costa, Yingqian Zhang
In many situations, simulation models are developed to handle complex real-world business optimisation problems.
no code implementations • 17 Jul 2019 • Paulo R. de O. da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak
We propose a Domain Adversarial Neural Network (DANN) approach to learn domain-invariant features that can be used to predict the RUL in the target domain.
no code implementations • 10 Jul 2019 • Paulo R. de O. da Costa, J. Rhuggenaath, Y. Zhang, A. Akcay, W. Lee, U. Kaymak
The TUSP is an important problem as it is used to determine the capacity of shunting yards and arises as a sub-problem of more general scheduling and planning problems.