Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
8-2005
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.
Discipline
Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering
Publication
MIC 2006: 6th Metaheuristics International Conference, August 22-26, Vienna
First Page
630
Last Page
636
Publisher
MIC
City or Country
Vienna
Citation
HALIM, Steven; WAN, Wee Chong; and LAU, Hoong Chuin.
Tuning Tabu Search strategies via visual diagnosis. (2005). MIC 2006: 6th Metaheuristics International Conference, August 22-26, Vienna. 630-636.
Available at: https://ink.library.smu.edu.sg/sis_research/363
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Artificial Intelligence and Robotics Commons, Operations Research, Systems Engineering and Industrial Engineering Commons