Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
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.
Download
No fulltext has been uploaded.
Conference Paper
| Published
| English
Author
Nikfarjam, Adel;
Neumann, Aneta;
Bossek, JakobLibreCat 
;
Neumann, Frank
;
Neumann, FrankEditor
Rudolph, Günter;
Kononova, Anna V.;
Aguirre, Hernán;
Kerschke, Pascal;
Ochoa, Gabriela;
Tu\v sar, Tea
Department
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
Publishing Year
Proceedings Title
Parallel Problem Solving from Nature (PPSN XVII)
forms.conference.field.series_title_volume.label
Lecture Notes in Computer Science
Page
237–249
ISBN
LibreCat-ID
Cite this
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. Parallel Problem Solving from Nature (PPSN XVII). Lecture Notes in Computer Science. Springer International Publishing; 2022:237–249. doi:10.1007/978-3-031-14714-2_17
Nikfarjam, A., Neumann, A., Bossek, J., & Neumann, F. (2022). Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tu\v sar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp. 237–249). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_17
@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={10.1007/978-3-031-14714-2_17}, 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} }
Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” In Parallel Problem Solving from Nature (PPSN XVII), 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. https://doi.org/10.1007/978-3-031-14714-2_17.
A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem,” in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 237–249, doi: 10.1007/978-3-031-14714-2_17.
Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249, doi:10.1007/978-3-031-14714-2_17.
Google Scholar
ISBN Search