Kenneth N. Reid

Kenneth N. Reid
Michigan State University | MSU · Department of Animal Science

PhD

About

19
Publications
5,308
Reads
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20
Citations
Introduction
Education
May 2015 - July 2019
University of Stirling
Field of study
  • Computing Science
August 2009 - July 2013
University of Stirling
Field of study
  • Computing Science

Publications

Publications (19)
Conference Paper
Full-text available
Genetic improvement is a search technique that aims to improve a given acceptable solution to a problem. In this paper, we present the novel use of genetic improvement to find problem-specific optimized LLVM pass sequences. We develop a pass-level patch representation in the linear genetic programming framework, Shackleton, to evolve the modificati...
Preprint
Full-text available
Genetic improvement is a search technique that aims to improve a given acceptable solution to a problem. In this paper, we present the novel use of genetic improvement to find problem-specific optimized LLVM pass sequences. We develop a pass-level patch representation in the linear genetic programming framework, Shackleton, to evolve the modificati...
Preprint
Full-text available
In this paper we introduce Shackleton as a generalized framework enabling the application of linear genetic programming -- a technique under the umbrella of evolutionary algorithms -- to a variety of use cases. We also explore here a novel application for this class of methods: optimizing sequences of LLVM optimization passes. The algorithm underpi...
Poster
Full-text available
The video game Factorio by Wube Software*, has a myriad of gameplay scenarios which are analogous to real-world problems, and is a useful simulator for developing solutions for them. In this paper we define the logistic transport belt problem, we provide an interface to allow optimizers in any programming language to interact with Factorio, and we...
Poster
Full-text available
LLVM IR (low-level virtual machine intermediate representation) is an intermediate step in the compilation of computer code. LLVM compilers allow optimization by using a sequence of steps (passes) to improve run-time or other criteria. Genetic Programming (GP) is an algorithm that is inspired by the natural selection process and can automatically g...
Preprint
Full-text available
Efficient optimization of resources is paramount to success in many problems faced today. In the field of operational research the efficient scheduling of employees; packing of vans; routing of vehicles; logistics of airlines and transport of materials can be the difference between emission reduction or excess, profits or losses and feasibility or...
Article
Full-text available
There is a growing interest among quantitative geneticists and animal breeders in the use of deep learning (DL) for genomic prediction. However, the performance of DL is affected by hyperparameters that are typically manually set by users. These hyperparameters do not simply specify the architecture of the model, they are also critical for the effi...
Preprint
Full-text available
There is a growing interest among quantitative geneticists and animal breeders in the use of deep learning (DL) for genomic prediction. However, the performance of DL is affected by hyperparameters that are typically manually set by users. These hyperparameters do not simply specify the architecture of the model, they are also critical for the effi...
Conference Paper
Full-text available
Employee scheduling problems are of critical importance to large businesses. These problems are hard to solve due to large numbers of conflicting constraints. While many approaches address a subset of these constraints, there is no single approach for simultaneously addressing all of them. We hybridise 'Evolutionary Ruin & Stochastic Recreate' and...
Thesis
Full-text available
Optimising resources and making considerate decisions are central concerns in any responsible organisation aiming to succeed in efficiently achieving their goals. Careful use of resources can have positive outcomes in the form of fiscal savings, improved service levels, better quality products, improved awareness of diminishing returns and general...
Conference Paper
Full-text available
For decades, since the inception of the field, scheduling problems have been solved with a variety of techniques. Many proven algorithms to these problems exist; however, there is no single method to solve all the vast variety of problems that exist across many sub-fields with differing datasets. In this paper we apply Evolutionary Ruin & Stochasti...
Conference Paper
Full-text available
This paper describes a Variable Neighbourhood Search (VNS) combined with Metropolis-Hastings acceptance to tackle a highly constrained workforce scheduling problem typical of field service operations (FSO) companies. A refined greedy algorithm is firstly designed to create an initial solution which meets all hard constraints and satisfies some of t...
Poster
Full-text available
The Problem of Exploring a Vast, Highly Constrained Search space. In our case study, up to 150 employees are allocated shifts by line managers over hundreds of areas. While this approach is successful at meeting hard constraints including contractual requirements and meeting demand requirements, the solutions produced are not consistently close to...

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