Use of machine learning techniques to model wind damage to forests
Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...
Roll Project Job Shop scheduling benchmark problems.
Dataset
Hart, E. & Sim, K. (2015)
Roll Project Job Shop scheduling benchmark problems. doi:10.17869/ENU.2015.9365
This document describes two sets of benchmark problem instances for the job shop scheduling problem. Each set of instances is supplied as a compressed (zipped) archive contain...
Novel Hyper-heuristics Applied to the Domain of Bin Packing
Thesis
Sim, K. Novel Hyper-heuristics Applied to the Domain of Bin Packing. (Thesis)
Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/id/eprint/7563
Principal to the ideology behind hyper-heuristic research is the desire to increase the level of generality of heuristic procedures so that they can be easily applied to a wid...
Roll Project Rich Vehicle Routing benchmark problems.
Dataset
Hart, E. & Sim, K. (2015)
Roll Project Rich Vehicle Routing benchmark problems. doi:10.17869/ENU.2015.9367
This document describes a large set of Benchmark Problem Instances for the Rich Vehicle Routing Problem. All files are supplied as a single compressed (zipped) archive contain...