Print Email Facebook Twitter A Robust Solution to Train Shunting using Decision Trees Title A Robust Solution to Train Shunting using Decision Trees Author Bao, Shiwei (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Verwer, Sicco (mentor) de Weerdt, Mathijs (mentor) Degree granting institution Delft University of Technology Date 2018-10-29 Abstract This research tackles the Train Unit Shunting Problem (TUSP) in train maintenance service sites. Many researches focus on producing feasible solutions, but only a few of them concentrate on the robustness of solutions. In reality, it is preferred to generate robust plans against unpredictable disturbances. Besides, the approach is expected to replan if disturbances occur while performing the plan. We propose this Decision Tree (DT)-based sequential approach (DTS) that solves the TUSP by sequentially making a sub-decision according to the DT prediction. It generates solutions that are both feasible and robust. Furthermore, it operates fast using the pre-trained model. We conduct experiments and compare its performance with a heuristic algorithm and the Local Search algorithm (LS). The proposed approach DTS solves fewer problems than LS and the heuristic, but it outperforms others by generating more robust solutions. Subject train shuntingdecision treesRobust To reference this document use: http://resolver.tudelft.nl/uuid:9acb3bd1-1ffb-4ebb-b886-f10c7291b101 Part of collection Student theses Document type master thesis Rights © 2018 Shiwei Bao Files PDF FInal_Thesis_and_Report_S ... weiBAO.pdf 2.33 MB Close viewer /islandora/object/uuid:9acb3bd1-1ffb-4ebb-b886-f10c7291b101/datastream/OBJ/view