[{"citation":{"ieee":"A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem,” in <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, 2022, pp. 237–249, doi: <a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>.","apa":"Nikfarjam, A., Neumann, A., Bossek, J., &#38; Neumann, F. (2022). Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tu\\v sar (Eds.), <i>Parallel Problem Solving from Nature (PPSN XVII)</i> (pp. 237–249). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">https://doi.org/10.1007/978-3-031-14714-2_17</a>","short":"A. Nikfarjam, A. Neumann, J. Bossek, F. Neumann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tu\\v sar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 237–249.","chicago":"Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” In <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\\v sar, 237–249. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">https://doi.org/10.1007/978-3-031-14714-2_17</a>.","mla":"Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249, doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>.","bibtex":"@inproceedings{Nikfarjam_Neumann_Bossek_Neumann_2022, place={Cham}, series={Lecture Notes in Computer Science}, title={Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>}, booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer International Publishing}, author={Nikfarjam, Adel and Neumann, Aneta and Bossek, Jakob and Neumann, Frank}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tu\\v sar, Tea}, year={2022}, pages={237–249}, collection={Lecture Notes in Computer Science} }","ama":"Nikfarjam A, Neumann A, Bossek J, Neumann F. Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tu\\v sar T, eds. <i>Parallel Problem Solving from Nature (PPSN XVII)</i>. Lecture Notes in Computer Science. Springer International Publishing; 2022:237–249. doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>"},"place":"Cham","status":"public","editor":[{"full_name":"Rudolph, Günter","last_name":"Rudolph","first_name":"Günter"},{"full_name":"Kononova, Anna V.","last_name":"Kononova","first_name":"Anna V."},{"full_name":"Aguirre, Hernán","last_name":"Aguirre","first_name":"Hernán"},{"full_name":"Kerschke, Pascal","last_name":"Kerschke","first_name":"Pascal"},{"full_name":"Ochoa, Gabriela","last_name":"Ochoa","first_name":"Gabriela"},{"last_name":"Tu\\v sar","first_name":"Tea","full_name":"Tu\\v sar, Tea"}],"user_id":"102979","_id":"48894","publisher":"Springer International Publishing","page":"237–249","abstract":[{"lang":"eng","text":"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."}],"extern":"1","publication":"Parallel Problem Solving from Nature (PPSN XVII)","department":[{"_id":"819"}],"type":"conference","keyword":["Co-evolutionary algorithms","Evolutionary diversity optimisation","Quality diversity","Traveling thief problem"],"date_created":"2023-11-14T15:59:00Z","date_updated":"2023-12-13T10:49:51Z","publication_status":"published","publication_identifier":{"isbn":["978-3-031-14714-2"]},"author":[{"last_name":"Nikfarjam","first_name":"Adel","full_name":"Nikfarjam, Adel"},{"full_name":"Neumann, Aneta","last_name":"Neumann","first_name":"Aneta"},{"id":"102979","full_name":"Bossek, Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","first_name":"Jakob"},{"last_name":"Neumann","first_name":"Frank","full_name":"Neumann, Frank"}],"title":"Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem","year":"2022","doi":"10.1007/978-3-031-14714-2_17","language":[{"iso":"eng"}],"series_title":"Lecture Notes in Computer Science"}]