Bandit-based Monte-Carlo planning for the single-machine total weighted tardiness scheduling problem

Gabriel Kronberger, Roland Braune

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationComputer Aided Systems Theory - EUROCAST 2007 - 11th International Conference on Computer Aided Systems Theory, Revised Selected Papers
PublisherSpringer Verlag
Pages837-844
Number of pages8
ISBN (Print)9783540758662
DOIs
Publication statusPublished - 2007
Event11th International Conference on Computer Aided Systems Theory, EUROCAST 2007 - Las Palmas de Gran Canaria, Spain
Duration: 12 Feb 200716 Feb 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4739 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Computer Aided Systems Theory, EUROCAST 2007
CountrySpain
CityLas Palmas de Gran Canaria
Period12.02.200716.02.2007

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