Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
July 28, 2022 ยท Declared Dead ยท ๐ PPSN 2022
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Authors
Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann
arXiv ID
2207.14036
Category
cs.NE: Neural & Evolutionary
Citations
0
Venue
PPSN 2022
Last Checked
4 months ago
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 the literature.
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