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Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics

Urquhart, Neil; Hart, Emma

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Abstract

Quality-diversity (QD) methods such as MAP-Elites have been demonstrated to be useful in the domain of combinatorial optimisation due to their ability to generate a large set of solutions to a single-objective problem that are diverse with respect to user-defined features of interest. However, filling a MAP-Elites container with solutions can require careful design of operators to ensure complete exploration of the feature-space. Working in the domain of urban logistics, we propose two methods to increase exploration. Firstly, we exploit multiple decodings of the same genome which can generate different offspring from the same parent solution. Secondly, we make use of a multiple mutation operators to generate offspring from a parent, using a multi-armed bandit algorithm to adaptively select the best operator during the search. Our results on a set of 48 instances show that both the number of solutions within the container and the qd score of the container (indicating quality) can be significantly increased compared to the standard MAP-Elites approach.

Presentation Conference Type Conference Paper (Published)
Conference Name Evo Applications 2023
Start Date Apr 12, 2023
End Date Apr 14, 2023
Acceptance Date Jan 18, 2023
Online Publication Date Apr 8, 2023
Publication Date Apr 10, 2023
Deposit Date Jan 27, 2023
Publicly Available Date Apr 9, 2024
Publisher Springer
Volume 13989
Pages 35-52
Series Title Lecture Notes in Computer Science
Series Number 13989
Series ISSN 0302-9743
Book Title Applications of Evolutionary Computation – 26th International Conference, EvoApplications 2023
ISBN 9783031302282
DOI https://doi.org/10.1007/978-3-031-30229-9
Keywords Artificial Intelligence ;Machine Learning; Evolutionary optimization; Evolutionary Computation; Meta-heuristics; Swarm Intelligence; Computational Intelligence ;Bio-Inspired Algorithms; Soft Computing; signal processing; optimization problems; optimizatio
Related Public URLs https://link.springer.com/book/9783031302282

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Improving The Size And Quality Of MAP-Elites Containers Via Multiple Emitters And Decoders For Urban Logistics (accepted version) (429 Kb)
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