TY - GEN
T1 - Diversity Management in Evolutionary Dynamic Optimization
AU - Werth, Bernhard
AU - Karder, Johannes
AU - Wagner, Stefan
AU - Affenzeller, Michael
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - The retention of diversity of genetic information is an important aspect of many population-based evolutionary optimizers. With the increasing relevance of dynamic optimization, where live data is streamed directly into a running optimization system, this algorithmic facet gains new importance. This study compares five different strategies for handling diversity in genetic algorithms in a dynamic open-ended optimization scenario. Using the traveling salesman problem as a benchmark, the algorithmic variations are compared and analyzed with respect to their performance and retained diversity. Results indicate that convergence patterns behave differently from static optimization and several algorithm features that are well understood for static optimization may have unintended consequences in dynamic scenarios.
AB - The retention of diversity of genetic information is an important aspect of many population-based evolutionary optimizers. With the increasing relevance of dynamic optimization, where live data is streamed directly into a running optimization system, this algorithmic facet gains new importance. This study compares five different strategies for handling diversity in genetic algorithms in a dynamic open-ended optimization scenario. Using the traveling salesman problem as a benchmark, the algorithmic variations are compared and analyzed with respect to their performance and retained diversity. Results indicate that convergence patterns behave differently from static optimization and several algorithm features that are well understood for static optimization may have unintended consequences in dynamic scenarios.
KW - dynamic optimization
KW - evolutionary algorithms
KW - genetic algorithms
UR - https://www.scopus.com/pages/publications/105004253035
U2 - 10.1007/978-3-031-82949-9_13
DO - 10.1007/978-3-031-82949-9_13
M3 - Conference contribution
AN - SCOPUS:105004253035
SN - 9783031829512
T3 - Lecture Notes in Computer Science
SP - 140
EP - 147
BT - Computer Aided Systems Theory - EUROCAST 2024 - 19th International Conference, 2024, Revised Selected Papers
A2 - Quesada-Arencibia, Alexis
A2 - Affenzeller, Michael
A2 - Moreno-Díaz, Roberto
PB - Springer
T2 - 19th International Conference on Computer Aided Systems Theory, EUROCAST 2024
Y2 - 25 February 2024 through 1 March 2024
ER -