Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/136884
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Type: Conference paper
Title: Co-evolutionary Diversity Optimisation for the Traveling Thief Problem
Author: Nikfarjam, A.
Neumann, A.
Bossek, J.
Neumann, F.
Citation: Lecture Notes in Artificial Intelligence, 2022 / Rudolph, G., Kononova, A.V., Aguirre, H.E., Kerschke, P., Ochoa, G., Tusar, T. (ed./s), vol.13398, pp.237-249
Publisher: Springer
Publisher Place: Online
Issue Date: 2022
Series/Report no.: Lecture Notes in Computer Science; 13398
ISBN: 9783031147135
ISSN: 0302-9743
1611-3349
Conference Name: International Conference on Parallel Problem Solving from Nature (PPSN) (10 Sep 2022 - 14 Sep 2022 : Dortmund, Germany)
Editor: Rudolph, G.
Kononova, A.V.
Aguirre, H.E.
Kerschke, P.
Ochoa, G.
Tusar, T.
Statement of
Responsibility: 
Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann
Abstract: Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity optimisation). In this study, we introduce a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component traveling thief problem. The results show the capability of the co-evolutionary algorithm to achieve significantly higher diversity compared to the baseline evolutionary diversity algorithms from the literature.
Keywords: Quality diversity; Co-evolutionary algorithms; Evolutionary diversity optimisation; Traveling thief problem
Rights: © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
DOI: 10.1007/978-3-031-14714-2_17
Grant ID: http://purl.org/au-research/grants/arc/DP190103894
http://purl.org/au-research/grants/arc/FT200100536
Published version: https://link.springer.com/book/10.1007/978-3-031-14714-2
Appears in Collections:Computer Science publications

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