DocumentCode
2731297
Title
An ant algorithm hyperheuristic for the project presentation scheduling problem
Author
Burke, Edmund ; Kendall, Graham ; Silva, Dario Landa ; O´Brien, Ross ; Soubeiga, E.
Author_Institution
Sch. of Comput. Sci. & Inf. Technol., Nottingham Univ., UK
Volume
3
fYear
2005
fDate
2-5 Sept. 2005
Firstpage
2263
Abstract
Ant algorithms have generated significant research interest within the search/optimization community in recent years. Hyperheuristic research is concerned with the development of "heuristics to choose heuristics" in an attempt to raise the level of generality at which optimization systems can operate. In this paper the two are brought together. An investigation of the ant algorithm as a hyperheuristic is presented and discussed. The results are evaluated against other hyperheuristic methods, when applied to a real world scheduling problem.
Keywords
heuristic programming; optimisation; scheduling; search problems; ant algorithm; hyperheuristic methods; project presentation scheduling; scheduling problem; Biological cells; Computer science; Decision support systems; Genetic algorithms; Information technology; Optimization methods; Processor scheduling; Scheduling algorithm; Space exploration; Technology planning;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN
0-7803-9363-5
Type
conf
DOI
10.1109/CEC.2005.1554976
Filename
1554976
Link To Document