Publication Type
Book Chapter
Version
acceptedVersion
Publication Date
12-2007
Abstract
While designing working metaheuristics can be straightforward, tuning them to solve the underlying combinatorial optimization problem well can be tricky. Several tuning methods have been proposed but they do not address the new aspect of our proposed classification of the metaheuristic tuning problem: tuning search strategies. We propose a tuning methodology based on Visual Diagnosis and a generic tool called Visualizer for Metaheuristics Development Framework(V-MDF) to address specifically the problem of tuning search (particularly Tabu Search) strategies. Under V-MDF, we propose the use of a Distance Radar visualizer where the human and computer can collaborate to diagnose the occurrence of negative incidents along the search trajectory on a set of training instances, and to perform remedial actions on the fly. Through capturing and observing the outcomes of actions in a Rule-Base, the user can then decide how to tune the search strategy effectively for subsequent use.
Keywords
Metaheuristics, Software Framework, Tuning Problem, Visualization
Discipline
Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering
Publication
Metaheuristics: Progress in complex systems optimization
Volume
39
Editor
Karl F. Doerner, M. Gendreau, P. Greistorfer, W. Gutjahr, R. F. Hartl, and M. Reimann
First Page
365
Last Page
388
ISBN
9780387719214
Identifier
10.1007/978-0-387-71921-4_19
Publisher
Springer Verlag
City or Country
New York
Citation
HALIM, Steven and LAU, Hoong Chuin.
Tuning Tabu Search strategies via visual diagnosis. (2007). Metaheuristics: Progress in complex systems optimization. 39, 365-388.
Available at: https://ink.library.smu.edu.sg/sis_research/238
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1007/978-0-387-71921-4_19
Included in
Artificial Intelligence and Robotics Commons, Operations Research, Systems Engineering and Industrial Engineering Commons