Dr Neil Urquhart N.Urquhart@napier.ac.uk
Lecturer
Dr Neil Urquhart N.Urquhart@napier.ac.uk
Lecturer
Prof Emma Hart E.Hart@napier.ac.uk
Professor
William Hutcheson
Quality-diversity algorithms such as MAP-Elites provide a means of supporting the users when finding and choosing solutions to a problem by returning a set of solutions which are diverse according to set of user-defined features. The number of solutions that can potentially be returned by MAP-Elites is controlled by a parameter that discretises the user-defined features into ‘bins’. For a fixed evaluation budget, increasing the number of bins increases user-choice, but at the same time, can lead to a reduction in overall quality of solutions while vice-versa, decreasing the number of bins can lead to higher-quality solutions at the expense of reducing choice. The goal of this paper it to explicitly quantify this trade-off, through a study of the application of Map-Elites to a Workforce Scheduling and Routing problem, using a large realistic instances based in London. We note that for the problems under consideration 30 bins or above maximises coverage (and therefore choice to the end user), whilst fewer bins maximises performance.
Urquhart, N., Hart, E., & Hutcheson, W. (2019, April). Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. Presented at EvoStar2019: International Conference on the Applications of Evolutionary Computation, Leipzig
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | EvoStar2019: International Conference on the Applications of Evolutionary Computation |
Start Date | Apr 24, 2019 |
End Date | Apr 26, 2019 |
Acceptance Date | Jan 5, 2019 |
Online Publication Date | Mar 30, 2019 |
Publication Date | Mar 30, 2019 |
Deposit Date | Jan 9, 2019 |
Publicly Available Date | Mar 30, 2019 |
Publisher | Springer |
Pages | 49-63 |
Series Title | Lecture Notes in Computer Science |
Series Number | 11454 |
Series ISSN | 0302-9743 |
Book Title | EvoApplications 2019: Applications of Evolutionary Computation |
ISBN | 978-3-030-16691-5 |
DOI | https://doi.org/10.1007/978-3-030-16692-2_4 |
Keywords | MAP-Elites; Transportation; Illumination; WSRP |
Public URL | http://researchrepository.napier.ac.uk/Output/1493024 |
Maximising User Choice
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