TY - GEN
T1 - Concurrent Evolution of Dynamic Single and Dual-Crane Scheduling Scenarios
AU - Karder, Johannes
AU - Werth, Bernhard
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 - Various approaches can be used to solve dynamic optimization problems. For example, on the one hand, optimization algorithms can be restarted every time the problem changes. As this results in a loss of optimization progress, algorithms can on the other hand also be implemented in an open-ended way, and to adapt to changing problem data during the run. Some problem updates cause fundamental changes to the optimization scenario. This paper describes different strategies to evolve solutions for such problems with scenario changes in the context of crane scheduling operations. It shows that simply ignoring such changes has negative effects on optimizer convergence, and compares the convergence behavior of five different strategies that can be applied when switches between different scenarios occur.
AB - Various approaches can be used to solve dynamic optimization problems. For example, on the one hand, optimization algorithms can be restarted every time the problem changes. As this results in a loss of optimization progress, algorithms can on the other hand also be implemented in an open-ended way, and to adapt to changing problem data during the run. Some problem updates cause fundamental changes to the optimization scenario. This paper describes different strategies to evolve solutions for such problems with scenario changes in the context of crane scheduling operations. It shows that simply ignoring such changes has negative effects on optimizer convergence, and compares the convergence behavior of five different strategies that can be applied when switches between different scenarios occur.
KW - dual-crane scheduling
KW - dynamic optimization
KW - open-ended optimization
KW - single-crane scheduling
UR - https://www.scopus.com/pages/publications/105004413545
U2 - 10.1007/978-3-031-83885-9_4
DO - 10.1007/978-3-031-83885-9_4
M3 - Conference contribution
AN - SCOPUS:105004413545
SN - 9783031838873
T3 - Lecture Notes in Computer Science
SP - 38
EP - 49
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 -