Rigorous analyses for the combination of ant colony optimization and local search
Date
2008
Authors
Neumann, F.
Sudholt, D.
Witt, C.
Editors
Dorigo, M.
Birattari, M.
Blum, C.
Clerc, M.
Stutzle, T.
Winfield, A.F.T.
Birattari, M.
Blum, C.
Clerc, M.
Stutzle, T.
Winfield, A.F.T.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Ant Colony Optimization and Swarm Intelligence: 6th International Conference, ANTS 2008, Brussels, Belgium, September 22-24, 2008: Proceedings / M. Dorigo... et al. (eds.), pp.132-143
Statement of Responsibility
Frank Neumann, Dirk Sudholt, and Carsten Witt
Conference Name
International Conference on Ant Colony Optimization and Swarm Intelligence (6th : 2008 : Brussels, Belgium)
Abstract
Ant colony optimization (ACO) is a metaheuristic that produces good results for a wide range of combinatorial optimization problems. Often such successful applications use a combination of ACO and local search procedures that improve the solutions constructed by the ants. In this paper, we study this combination from a theoretical point of view and point out situations where introducing local search into an ACO algorithm enhances the optimization process significantly. On the other hand, we illustrate the drawback that such a combination might have by showing that this may prevent an ACO algorithm from obtaining optimal solutions.
School/Discipline
Dissertation Note
Provenance
Description
Also published as a journal article: Lecture notes in computer science, 2008; 5217:132-143
Access Status
Rights
© Springer-Verlag Berlin Heidelberg 2008