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Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem.

Urquhart, Neil; Hart, Emma; Hutcheson, William

Authors

William Hutcheson



Abstract

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.

Citation

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

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