TY - GEN
T1 - Bandit-based Monte-Carlo planning for the single-machine total weighted tardiness scheduling problem
AU - Kronberger, Gabriel
AU - Braune, Roland
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - The balance of exploration and exploitation is the essence of any successful meta-heuristic. The Multi-armed Bandit Problem represents a simple form of this general dilemma. This paper describes two heuristic optimization methods that use a simple yet efficient allocation strategy for the bandit problem called UCB1 to control the optimization process. The algorithms are applied to the well known Single Machine Total Weighted Tardiness Problem and the results compared to the results of other successful meta-heuristics for this scheduling problem.
AB - The balance of exploration and exploitation is the essence of any successful meta-heuristic. The Multi-armed Bandit Problem represents a simple form of this general dilemma. This paper describes two heuristic optimization methods that use a simple yet efficient allocation strategy for the bandit problem called UCB1 to control the optimization process. The algorithms are applied to the well known Single Machine Total Weighted Tardiness Problem and the results compared to the results of other successful meta-heuristics for this scheduling problem.
UR - http://www.scopus.com/inward/record.url?scp=38449109866&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-75867-9_105
DO - 10.1007/978-3-540-75867-9_105
M3 - Conference contribution
SN - 9783540758662
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 837
EP - 844
BT - Computer Aided Systems Theory - EUROCAST 2007 - 11th International Conference on Computer Aided Systems Theory, Revised Selected Papers
PB - Springer
T2 - 11th International Conference on Computer Aided Systems Theory, EUROCAST 2007
Y2 - 12 February 2007 through 16 February 2007
ER -